title: Defamation

text: There can be regional statutes that may differ from the national norm. For example, in the United States, criminal defamation is generally limited to the living. However, there are 7 states (Idaho, Kansas, Louisiana, Nevada, North Dakota, Oklahoma, Utah) that have criminal statutes regarding defamation of the dead.


title: Defamation

text: The Organization for Security and Co-operation in Europe (OSCE) has also published a detailed database on criminal and civil defamation provisions in 55 countries, including all European countries, all member countries of the Commonwealth of Independent States, America, and Canada.


title: Defamation

text: In a 2012 ruling on a complaint filed by a broadcaster who had been imprisoned for violating Philippine libel law, the United Nations Commission on Human Rights held that the criminalisation of libel without provision of a public figure doctrine – as in Philippine criminal law – violates freedom of expression and is inconsistent with Article 19 of the International Covenant on Civil and Political Rights.


title: Defamation

text: Questions of group libel have been appearing in common law for hundreds of years. One of the earliest known cases of a defendant being tried for defamation of a group was the case of "R v Orme and Nutt" (1700). In this case, the jury found that the defendant was guilty of libeling several subjects, though they did not specifically identify who these subjects were. A report of the case told that the jury believed that "where a writing ... inveighs against mankind in general, or against a particular order of men, as for instance, men of the gown, this is no libel, but it must descend to particulars and individuals to make it libel." This jury believed that only individuals who believed they were specifically defamed had a claim to a libel case. Since the jury was unable to identify the exact people who were being defamed, there was no cause to identify the statements were a libel.


title: Defamation

text: Another early English group libel which has been frequently cited is "King v. Osborne" (1732). In this case, the defendant was on trial "for printing a libel reflecting upon the Portuguese Jews". The printing in question claimed that Jews who had arrived in London from Portugal burned a Jewish woman to death when she had a child with a Christian man, and that this act was common. Following Osborne's anti-Semitic publication, several Jews were attacked. Initially, the judge seemed to believe the court could do nothing since no individual was singled out by Osborne's writings. However, the court concluded that "since the publication implied the act was one Jews frequently did, the whole community of Jews was defamed." Though various reports of this case give differing accounts of the crime, this report clearly shows a ruling based on group libel. Since laws restricting libel were accepted at this time because of its tendency to lead to a breach of peace, group libel laws were justified because they showed potential for an equal or perhaps greater risk of violence. For this reason, group libel cases are criminal even though most libel cases are civil torts.


title: Defamation

text: As of 2017, at least 130 UNESCO member states retained criminal defamation laws. In 2017, the Organization for Security and Co-operation in Europe (OSCE) Office of the Representative on Freedom of the Media issued a report on criminal defamation and anti-blasphemy laws among its member states, which found that defamation is criminalised in nearly three-quarters (42) of the 57 OSCE participating states. Many of the laws pertaining to defamation include specific provisions for harsher punishment for speech or publications critical of heads of state, public officials, state bodies and the state itself. The OSCE report also noted that blasphemy and religious insult laws exist in around one third of OSCE participating states; many of these combine blasphemy and religious insult with elements of hate speech legislation.


title: Defamation

text: In Africa, at least four member states decriminalised defamation between 2012 and 2017. The ruling by the African Court on Human and Peoples' Rights in "Lohé Issa Konaté v. The Republic of Burkina Faso" set a precedent in the region against imprisonment as a legitimate penalty for defamation, framing it as a violation of the African Charter on Human and Peoples' Rights (ACHPR), the International Covenant on Civil and Political Rights (ICCPR) and the treaty of the Economic Community of West African States (ECOWAS).


title: Defamation

text: Countries in every region have moved to further extend criminal defamation law to online content. Cybercrime and anti-terrorism laws passed throughout the world have led to bloggers appearing before courts, with some serving time in prison.


title: Defamation

text: In a variety of Common Law jurisdictions, criminal laws prohibiting protests at funerals, sedition, false statements in connection with elections, and the use of profanity in public, are also often used in contexts similar to criminal libel actions. The boundaries of a court's power to hold individuals in "contempt of court" for what amounts to alleged defamatory statements about judges or the court process by attorneys or other people involved in court cases is also not well established in many common law countries.


title: Defamation

text: While defamation torts are less controversial as they ostensibly involve plaintiffs seeking to protect their right to dignity and their reputation, criminal defamation is more controversial as it involves the state expressly seeking to restrict freedom of expression. Human rights organisations, and other organisations such as the Council of Europe and Organization for Security and Co-operation in Europe, have campaigned against strict defamation laws that criminalise defamation. The freedom of expression advocacy group Article 19 opposes criminal defamation, arguing that civil defamation laws providing defences for statements on matters of public interest are better compliant with international human rights law. The European Court of Human Rights has placed restrictions on criminal libel laws because of the freedom of expression provisions of the European Convention on Human Rights. One notable case was "Lingens v. Austria" (1986).


title: Defamation

text: The United Nations, OSCE, Organization of American States (OAS) and African Union Commission on Human and Peoples' Rights Special Rapporteurs for Freedom of Expression stated in a joint declaration in March 2017 that "general prohibitions on the dissemination of information based on vague and ambiguous ideas, including 'false news' or 'non-objective information', are incompatible with international standards for restrictions on freedom of expression ... and should be abolished."


title: Defamation

text: Note: This table lacks detail, to avoid potential copyright issues with the OSCE. Readers are advised to check the OSCE document instead.


title: Defamation

text: According to the Criminal Code of Albania, defamation is a crime. Slandering in the knowledge of falsity is subject to fines of from ALL (c. $350) to one million ALL (c. $). If the slandering occurs in public or damages multiple people, the fine is 40,000 ALL to three million ALL (c. $). In addition, defamation of authorities, public officials or foreign representatives (Articles 227, 239 to 241) are separate crimes with maximum penalties varying from one to three years of imprisonment.


title: Defamation

text: In Argentina, the crimes of calumny and injury are foreseen in the chapter "Crimes Against Honor" (Articles 109 to 117-bis) of the Penal Code. Calumny is defined as "the false imputation to a determined person of a concrete crime that leads to a lawsuit" (Article 109). However, expressions referring to subjects of public interest or that are not assertive do not constitute calumny. Penalty is a fine from 3,000 to 30,000 pesos. He who intentionally dishonor or discredit a determined person is punished with a penalty from 1,500 to 20,000 pesos (Article 110).


title: Defamation

text: He who publishes or reproduces, by any means, calumnies and injuries made by others, will be punished as responsible himself for the calumnies and injuries whenever its content is not correctly attributed to the corresponding source. Exceptions are expressions referring to subjects of public interest or that are not assertive (see Article 113). When calumny or injury are committed through the press, a possible extra penalty is the publication of the judicial decision at the expenses of the guilty (Article 114). He who passes to someone else information about a person that is included in a personal database and that one knows to be false, is punished with six months to 3 years in prison. When there is harm to somebody, penalties are aggravated by an extra half (Article 117 bis, §§ 2nd and 3rd).


title: Defamation

text: In Austria, the crime of defamation is foreseen by Article 111 of the Criminal Code. Related criminal offences include "slander and assault" (Article 115), that happens "if a person insults, mocks, mistreats or threatens will ill-treatment another one in public", and yet "malicious falsehood" (Article 297), defined as a false accusation that exposes someone to the risk of prosecution.


title: Defamation

text: In Azerbaijan, the crime of defamation (Article 147) may result in a fine up to "500 times the amount of minimum salaries", public work for up to 240 hours, correctional work for up to one year, or imprisonment of up to six months. Penalties are aggravated to up to three years of prison if the victim is falsely accused of having committed a crime "of grave or very grave nature" (Article 147.2). The crime of insult (Article 148) can lead to a fine of up to 1,000 times the minimum wage, or to the same penalties of defamation for public work, correctional work or imprisonment.


title: Defamation

text: According to the OSCE report on defamation laws, "Azerbaijan intends to remove articles on defamation and insult from criminal legislation and preserve them in the Civil Code".


title: Defamation

text: In Belgium, crimes against honor are foreseen in Chapter V of the Belgian Penal Code, Articles 443 to 453-bis. Someone is guilty of calumny "when law admits proof of the alleged fact" and of defamation "when law does not admit this evidence" (Article 443). The penalty is eight days to one year of imprisonment, plus a fine (Article 444). In addition, the crime of "calumnious denunciation" (Article 445) is punished with 15 days to six months in prison, plus a fine. In any of the crimes covered by Chapter V of the Penal Code, the minimum penalty may be doubled (Article 453-bis) "when one of the motivations of the crime is hatred, contempt or hostility of a person due to his or her intended race, colour of the skin, ancestry, national origin or ethnicity, nationality, gender, sexual orientation, marital status, place of birth, age, patrimony, philosophical or religious belief, present or future health condition, disability, native language, political belief, physical or genetical characteristic, or social origin".


title: Defamation

text: In Brazil, defamation is a crime, which is prosecuted either as "defamation" (three months to a year in prison, plus fine; Article 139 of the Penal Code), "calumny" (six months to two years in prison, plus fine; Article 138 of the PC) or "injury" (one to six months in prison, or fine; Article 140), with aggravating penalties when the crime is practiced in public (Article 141, item III) or against a state employee because of his regular duties. Incitation to hatred and violence is also foreseen in the Penal Code (incitation to a crime, Article 286). Moreover, in situations like bullying or moral constraint, defamation acts are also covered by the crimes of "illegal constraint" (Article 146 of the Penal Code) and "arbitrary exercise of discretion" (Article 345 of PC), defined as breaking the law as a vigilante.


title: Defamation

text: In Bulgaria, defamation is formally a criminal offence, but the penalty of imprisonment was abolished in 1999. Articles 146 (insult), 147 (criminal defamation) and 148 (public insult) of the Criminal Code prescribe a penalty of fine.


title: Defamation

text: The criminal portion of the law has been rarely applied, but it has been observed that, when treated as an indictable offence, it often appears to arise from statements made against an agent of the Crown, such as a police officer, a corrections officer, or a Crown attorney. In the most recent case, in 2012, an Ottawa restaurant owner was convicted of ongoing online harassment of a customer who had complained about the quality of food and service in her restaurant.


title: Defamation

text: According to an Organization for Security and Co-operation in Europe official report on defamation laws issued in 2005, 57 persons in Canada were accused of defamation, libel and insult, among which 23 were convicted – 9 to prison sentences, 19 to probation and one to a fine. The average period in prison was 270 days, and the maximum sentence was 4 years of imprisonment.


title: Defamation

text: In Croatia, the crime of insult prescribes a penalty of up to three months in prison, or a fine of "up to 100 daily incomes" (Criminal Code, Article 199). If the crime is committed in public, penalties are aggravated to up to six months of imprisonment, or a fine of "up to 150 daily incomes" (Article 199–2). Moreover, the crime of defamation occurs when someone affirms or disseminates false facts about other person that can damage his reputation. The maximum penalty is one year in prison, or a fine of up to 150 daily incomes (Article 200–1). If the crime is committed in public, the prison term can reach one year (Article 200–2). On the other hand, according to Article 203, there is an exemption for the application of the aforementioned articles (insult and defamation) when the specific context is that of a scientific work, literary work, work of art, public information conducted by a politician or a government official, journalistic work, or the defence of a right or the protection of justifiable interests, in all cases "provided that" the conduct was not aimed at damaging someone's reputation.


title: Defamation

text: In Chile, the crimes of calumny and slanderous allegation () are covered by Articles 412 to 431 of the Penal Code. Calumny is defined as "the false imputation of a determined crime and that can lead to a public prosecution" (Article 412). If the calumny is written and with publicity, penalty is "lower imprisonment" in its medium degree plus a fine of 11 to 20 "vital wages" when it refers to a crime, or "lower imprisonment" in its minimum degree plus a fine of six to ten "vital wages" when it refers to a misdemeanor (Article 413). If it is not written or with publicity, penalty is "lower imprisonment" in its minimum degree plus a fine of six to fifteen "vital wages" when it is about a crime, or plus a fine of six to ten "vital wages" when it is about a misdemeanor (Article 414).


title: Defamation

text: According to Article 25 of the Penal Code, "lower imprisonment" is defined as a prison term between 61 days and five years. According to Article 30, the penalty of "lower imprisonment" in its medium or minimum degrees carries with it also the suspension of the exercise of a public position during the prison term.


title: Defamation

text: Article 416 defines as "all expression said or action performed that dishonors, discredits or causes contempt". Article 417 defines broadly (grave slander), including the imputation of a crime or misdemeanor that cannot lead to public prosecution, and the imputation of a vice or lack of morality, which are capable of harming considerably the reputation, credit or interests of the offended person. "Grave slander" in written form or with publicity are punished with "lower imprisonment" in its minimum to medium degrees plus a fine of eleven to twenty "vital wages". Calumny or slander of a deceased person (Article 424) can be prosecuted by the spouse, children, grandchildren, parents, grandparents, siblings and heirs of the offended person. Finally, according to Article 425, in the case of calumnies and slander published in foreign newspapers, are considered liable all those who from Chilean territory sent articles or gave orders for publication abroad, or contributed to the introduction of such newspapers in Chile with the intention of propagating the calumny and slander.


title: Defamation

text: In the Chinese mainland, Article 246 of the Criminal Law of the People's Republic of China () makes serious defamation punishable by fixed-term imprisonment of not more than three years or criminal detention upon complaint, unless it is against the government.


title: Defamation

text: In areas administered by the Republic of China, Article 310 of the Criminal Code () criminalises defamation, held constitutional on 7 July 2000 by the Justices of the Constitutional Court, Judicial Yuan (). The court's reasoning in upholding the law was that, while Article 11 of the Constitution of the Republic of China protects freedom of speech, the right is "subject to suitable restraints" where this is necessary to "protect other fundamental rights, such as personal reputation and privacy". While Article 310 provides that an individual accused of criminal defamation is to be acquitted if they are able to prove the truth of the defamatory statement in question; the court interpreted this to mean that, even if the accused fails to demonstrate that the statement was true, they may not be convicted if they had reasonable grounds to believe that the statement was true when it was made and that the burden of proof still lies with the prosecution. The continued criminalisation of defamation in the Republic of China is controversial, with an editorial in the "Taipei Times" published in January 2022 arguing that prosecutors, being "a common asset of society", ought to "put all their efforts into major crimes rather than private disputes" and that criminal defamation "inappropriately" transforms the nations' courts into courts of "folk morality".


title: Defamation

text: According to the Czech Criminal Code, Article 184, defamation is a crime. Penalties may reach a maximum prison term of one year (Article 184–1) or, if the crime is committed through the press, film, radio, TV, publicly accessible computer network, or by "similarly effective" methods, the offender may stay in prison for up to two years or be prohibited of exercising a specific activity.


title: Defamation

text: However, only the most severe cases will be subject to criminal prosecution. The less severe cases can be solved by an action for apology, damages or injunctions.


title: Defamation

text: In Denmark, libel is a crime, as defined by Article 267 of the Danish Criminal Code, with a penalty of up to six months in prison or a fine, with proceedings initiated by the victim. In addition, Article 266-b prescribes a maximum prison term of two years in the case of public defamation aimed at a group of persons because of their race, colour, national or ethnic origin, religion or "sexual inclination".


title: Defamation

text: In Finland, defamation is a crime, according to the Criminal Code (Chapter 24, Sections 9 and 10), punishable with a fine, or, if aggravated, with up to two years' imprisonment or a fine. Defamation is defined as spreading a false report or insinuation apt to cause harm to a person, or otherwise disparaging someone. Defamation of the deceased may also constitute an offence if apt to cause harm to surviving loved ones. In addition, there is a crime called "dissemination of information violating personal privacy" (Chapter 24, Section 8), which consists in disseminating information, even accurate, in a way that is apt to harm someone's right to privacy. Information that may be relevant with regard to a person's conduct in public office, in business, or in a comparable position, or of information otherwise relevant to a matter of public interest, is not covered by this prohibition. Finnish criminal law has no provisions penalizing the defamation of corporate entities, only of natural persons.


title: Defamation

text: In France, defamation is a criminal offence defined as "the allegation or [the] allocation of a fact that damages the honor or reputation of the person or body to which the fact is imputed". A defamatory allegation is considered an insult if it does not include any facts or if the claimed facts cannot be verified.


title: Defamation

text: In German law, there is no distinction between libel and slander. , German defamation lawsuits are increasing. The relevant offences of Germany's Criminal Code are §90 (denigration of the Federal President), §90a (denigration of the [federal] State and its symbols), §90b (unconstitutional denigration of the organs of the Constitution), §185 ("insult"), §186 (defamation of character), §187 (defamation with deliberate untruths), §188 (political defamation with increased penalties for offending against paras 186 and 187), §189 (denigration of a deceased person), §192 ("insult" with true statements). Other sections relevant to prosecution of these offences are §190 (criminal conviction as proof of truth), §193 (no defamation in the pursuit of rightful interests), §194 (application for a criminal prosecution under these paragraphs), §199 (mutual insult allowed to be left unpunished), and §200 (method of proclamation).


title: Defamation

text: In Greece, the maximum prison term for defamation, libel or insult was five years, while the maximum fine was €15,000.


title: Defamation

text: The crime of insult (Article 361, § 1, of the Penal Code) may have led to up to one year of imprisonment or a fine, while unprovoked insult (Article


title: Defamation

text: 361-A, § 1) was punished with at least three months in prison. In addition, defamation may have resulted in up to two months in prison or a fine, while aggravated defamation could have led to at least three months of prison, plus a possible fine (Article 363) and deprivation of the offender's civil rights. Finally, disparaging the memory of a deceased person is punished with imprisonment of up to six months (Penal Code, Article 365).


title: Defamation

text: In India, a defamation case can be filed under either criminal law or civil law or cyber crime law, together or in sequence.


title: Defamation

text: According to the Constitution of India, the fundamental right to free speech (Article 19) is subject to "reasonable restrictions":


title: Defamation

text: Accordingly, for the purpose of criminal defamation, "reasonable restrictions" are defined in Section 499 of the Indian Penal Code, 1860. This section defines defamation and provides ten valid exceptions when a statement is not considered to be defamation. It says that defamation takes place, when someone "by words either spoken or intended to be read, or by signs or by visible representations, makes or publishes any imputation concerning any person intending to harm, or knowing or having reason to believe that such imputation will harm, the reputation of such person". The punishment is simple imprisonment for up to two years, or a fine, or both (Section 500).


title: Defamation

text: Some other offences related to false allegations: false statements regarding elections (Section 171G), false information (Section 182), false claims in court (Section 209), false criminal charges (Section 211).


title: Defamation

text: Some other offences related to insults: against public servants in judicial proceedings (Section 228), against religion or religious beliefs (Section 295A), against religious feelings (Section 298), against breach of peace (Section 504), against modesty of women (Section 509).


title: Defamation

text: According to the Indian Code of Criminal Procedure, 1973 defamation is prosecuted only upon a complaint (within six months from the act) (Section 199), and is a bailable, non-cognisable and compoundable offence (See: The First Schedule, Classification of Offences).


title: Defamation

text: According to the (revised) Defamation Act 2009, the last criminal offences (Sections 36–37, blasphemy) seem to have been repealed. The statute of limitations is one year from the time of first publication (may be extended to two years by the courts) (Section 38). See also: Blasphemy law in the Republic of Ireland, Censorship in the Republic of Ireland, Statute of Limitations in Ireland.


title: Defamation

text: The 2009 Act repeals the Defamation Act 1961, which had, together with the underlying principles of the common law of tort, governed Irish defamation law for almost half a century. The 2009 Act represents significant changes in Irish law, as many believe that it previously attached insufficient importance to the media's freedom of expression and weighed too heavily in support of the individual's right to a good name.


title: Defamation

text: According to "Defamation Prohibition Law" (1965), defamation can constitute either civil or criminal offence.


title: Defamation

text: As a civil offence, defamation is considered a tort case and the court may award a compensation of up to to the person targeted by the defamation, while the plaintiff does not have to prove a material damage.


title: Defamation

text: As a criminal offence, defamation is punishable by a year of imprisonment. In order to constitute a felony, defamation must be intentional and target at least two persons.


title: Defamation

text: In Italy, there used to be different crimes against honor. The crime of injury (Article 594 of the penal code) referred to the act of offending someone's honor in their presence and was punishable with up to six months in prison or a fine of up to €516. The crime of defamation (Article 595, Penal Code) refers to any other situation involving offending one's reputation before many persons, and is punishable with a penalty of up to a year in prison or up to €1,032 in fine, doubled to up to two years in prison or a fine of €2,065 if the offence consists in the attribution of a determined fact. When the offence happens by the means of the press or by any other means of publicity, or in a public demonstration, the penalty is of imprisonment from six months to three years, or a fine of at least €516. Both of them were "" crimes, that is, the victim had the right of choosing, in any moment, to stop the criminal prosecution by withdrawing the "" (a formal complaint), or even prosecute the fact only with a civil action with no "" and therefore no criminal prosecution at all. However, beginning from 15 January 2016, injury is no longer a crime, but a tort, while defamation is still considered a crime like before.


title: Defamation

text: Finally, Article 31 of the Penal Code establishes that crimes committed with abuse of power or with abuse of a profession or art, or with the violation of a duty inherent to that profession or art, lead to the additional penalty of a temporary ban in the


title: Defamation

text: Deliberately false accusations of defamation, as with any other crime, lead to the crime of calumny (Article 368, Penal Code), which, under the Italian legal system, is defined as the crime of falsely accusing, before the authorities, a person of a crime they did not commit.


title: Defamation

text: The Japanese Penal Code (note: translation from government, but still not official text) seems to prescribe these related offences:


title: Defamation

text: Additionally, there is an exception stemming from Article XXI of the Constitution concerning freedom of the press, which provides that media outlets can avoid liability for defamation if they reasonably believed the defamatory statements they published to be true.


title: Defamation

text: In Malaysia, defamation is both a tort and a criminal offence meant to protect the reputation and good name of a person. The principal statutes relied upon are the Defamation Act 1957 (Revised 1983) and the Penal Code. Following the practice of other common law jurisdictions like the United Kingdom, Singapore, and India, Malaysia relies on case law. In fact, the Defamation Act 1957 is similar with the English Defamaiton Act 1952. The Malaysian Penal Code is with the Indian and Singaporean Penal Codes.


title: Defamation

text: In Mexico, crimes of calumny, defamation and slanderous allegation () have been abolished in the Federal Penal Code as well as in fifteen states. These crimes remain in the penal codes of seventeen states, where penalty is, in average, from 1.1 years (for ones convicted for slanderous allegation) to 3.8 years in jail (for those convicted for calumny).


title: Defamation

text: In the Netherlands, defamation is mostly dealt with by lodging a civil complaint at the District Court. Article 167 of book 6 of the Civil Code holds: "When someone is liable towards another person under this Section because of an incorrect or, by its incompleteness, misleading publication of information of factual nature, the court may, upon a right of action (legal claim) of this other person, order the tortfeasor to publish a correction in a way to be set by court." If the court grants an injunction, the defendant is usually ordered to delete the publication or to publish a rectification statement.


title: Defamation

text: In Norway, defamation was a crime punished with imprisonment of up to six months or a fine (Penal Code, Chapter 23, § 246). When the offense is likely to harm one's "good name" and reputation, or exposes him to hatred, contempt or loss of confidence, the maximum prison term went up to one year, and if the defamation happens in print, in broadcasting or through an especially aggravating circumstance, imprisonment may have reached two years (§ 247). When the offender acts "against his better judgment", he was liable to a maximum prison term of three years (§ 248). According to § 251, defamation lawsuits must be initiated by the offended person, unless the defamatory act was directed to an indefinite group or a large number of persons, when it may also have been prosecuted by public authorities.


title: Defamation

text: Under the new Penal Code, decided upon by the Parliament in 2005, defamation would cease to exist as a crime. Rather, any person who believes he or she has been subject to defamation will have to press civil lawsuits. The Criminal Code took effect on 1 October 2015.


title: Defamation

text: In Poland, defamation is a crime that consists of accusing someone of a conduct that may degrade him in public opinion or expose him "to the loss of confidence necessary for a given position, occupation or type of activity". Penalties include fine, limitation of liberty and imprisonment for up to a year (Article 212.1 of the Criminal Code). The penalty is more severe when the offence happens through the media (Article 212.2). When the insult is public and aims at offending a group of people or an individual because of his or their nationality, ethnicity, race, religion or lack of religion, the maximum prison term is three years.


title: Defamation

text: In Portugal, defamation crimes are: "defamation" (article 180 of the Penal Code; up to six months in prison, or a fine of up to 240 days), "injuries" (art. 181; up to three months in prison, or a fine up to 120 days), and "offence to the memory of a deceased person" (art. 185; up to 6 months in prison or a fine of up 240 days). Penalties are aggravated in cases with publicity (art. 183; up to two years in prison or at least 120 days of fine) and when the victim is an authority (art.184; all other penalties aggravated by an extra half). There is yet the extra penalty of "public knowledge of the court decision" (costs paid by the defamer) (art. 189 of Penal Code) and also the crime of "incitement of a crime" (article 297; up to three years in prison, or fine).


title: Defamation

text: Title thirteen of the Revised Penal Code of the Philippines addresses "Crimes Against Honor". Chapter one of that title addresses libel and slander. Libel is defined as "public and malicious imputation of a crime, or of a vice or defect, real or imaginary, or any act, omission, condition, status, or circumstance tending to cause the dishonor, discredit, or contempt of a natural or juridical person, or to blacken the memory of one who is dead". Slander is defined as oral defamation. Slander by deed is defined as "any act not included and punished in this title, which shall cast dishonor, discredit or contempt upon another person". Penalties of fine or imprisonment are specified for these crimes and for the threat of libel. A notable characteristic of these crimes under Philippine law is the specification that they apply to imputations both real and imaginary. The United Nations Human Rights Committee ruled in 2012 that the libel law of the Philippines was inconsistent with Article 19 of the International Covenant on Civil and Political Rights as well as urging that "State parties [to the Covenant] should consider the decriminalisation of libel".


title: Defamation

text: In Saudi Arabia, defamation of the state, or a past or present ruler, is punishable under terrorism legislation. In a 2015 case, a Saudi writer was arrested for defaming a former ruler of the country. Reportedly, under a [2014] counterterrorism law, "actions that 'threaten Saudi Arabia's unity, disturb public order, or defame the reputation of the state or the king' are considered acts of terrorism. The law decrees that a suspect can be held incommunicado for 90 days without the presence of their lawyer during the initial questioning."


title: Defamation

text: In South Korea, both true and false statements can be considered defamation. The penalties increase for false statements. It is also possible for a person to be criminally defamed when they are no longer alive.


title: Defamation

text: Criminal defamation occurs when a public statement damages the subject's reputation, unless the statement was true and presented solely for the public interest. In addition to criminal law, which allows for imprisonment (up to seven years in case the allegations are false) and monetary fines, in South Korea one can also sue for damages with civil actions. Generally, criminal actions proceed civil ones with South Korean police as judicial investigators.


title: Defamation

text: In the former Soviet Union, defamatory insults can "only constitute a criminal offence, not a civil wrong".


title: Defamation

text: In Spain, the crime of calumny (Article 205 of the Penal Code) consists of accusing someone of a crime knowing the falsity of the accusation, or with a reckless contempt for truth. Penalties for cases with publicity are imprisonment from six months to two years or a fine of 12 to 24 months-fine, and for other cases only a fine of six to twelve months-fine (Article 206). Additionally, the crime of injury (Article 208 of the Penal Code) consists of hurting someone's dignity, depreciating his reputation or injuring his self-esteem, and is only applicable if the offence, by its nature, effects and circumstances, is considered by the general public as strong. Injury has a penalty of fine from three to seven months-fine, or from six to fourteen months-fine when it is strong and with publicity. According to Article 216, an additional penalty to calumny or injury may be imposed by the judge, determining the publication of the judicial decision (in a newspaper) at the expenses of the defamer.


title: Defamation

text: In Sweden, denigration () is criminalised by Chapter 5 of the Criminal Code. Article 1 regulates defamation () and consists of pointing out someone as a criminal or as "having a reprehensible way of living", or of providing information about them "intended to cause exposure to the disrespect of others". The penalty is a fine. It is generally not a requirement that the statements are untrue; it is enough if they statements are meant to be vilifying.


title: Defamation

text: Article 2 regulates gross defamation () and has a penalty of up to two years in prison or a fine. In judging if the crime is gross, the court should consider whether the information, because of its content or the scope of its dissemination, is calculated to produce "serious damage". For example, if it can be established that the defendant knowingly conveyed untruths. Article 4 makes it a crime to defame a deceased person according to Article 1 or 2. Most obviously, the paragraph is meant to make it illegal to defame someone's parents as a way to bypass the law.


title: Defamation

text: Article 3 regulates other insulting behaviour (), not characterised under Article 1 or 2, and is punishable with a fine or, if it is gross, with up to six months of prison or a fine. While an act of defamation involves a third person, it is not a requirement for insulting behaviour.


title: Defamation

text: Under exemptions in the Freedom of the Press Act, Chapter 7, both criminal and civil lawsuits may be brought to court under the laws on denigration.


title: Defamation

text: In Switzerland, the crime of wilful defamation is punished with a maximum term of three years in prison, or with a fine of at least thirty days' fine, according to Article 174-2 of the Swiss Criminal Code. There is wilful defamation when the offender knows the falsity of his/her allegations and intentionally looks to ruin the reputation of one's victim (see Articles 174-1 and 174–2).


title: Defamation

text: On the other hand, defamation is punished only with a maximum monetary penalty of 180 daily penalty units (Article 173–1). When it comes to a deceased or absent person, there is a limitation to enforce the law up to 30 years (after the death).


title: Defamation

text: With the rise of the internet, and also intranets (closed computer networks), defamatory statements may be communicated on webpages or internal memos, without reaching the attention of the courts. Such "closet defamation" may be used to conceal other criminal or negligent acts.


title: Defamation

text: Criminal defamation charges in Thailand under Section 326 of the Criminal Code are frequently used to censor journalists and activists critical of human rights circumstances for workers in the country.


title: Defamation

text: The United Kingdom abolished criminal libel on 12 January 2010 by section 73 of the Coroners and Justice Act 2009. There were only a few instances of the criminal libel law being applied. Notably, the Italian anarchist Errico Malatesta was convicted of criminal libel for denouncing the Italian state agent Ennio Belelli in 1912.


title: Defamation

text: Under English common law, proving the truth of the allegation was originally a valid defence only in civil libel cases. Criminal libel was construed as an offence against the public at large based on the tendency of the libel to provoke breach of peace, rather than being a crime based upon the actual defamation "per se"; its veracity was therefore considered irrelevant. Section 6 of the Libel Act 1843 allowed the proven truth of the allegation to be used as a valid defence in criminal libel cases, but only if the defendant also demonstrated that publication was for the "public benefit".


title: Defamation

text: Less than half of American states have criminal defamation laws, but the applicability of those laws is limited by the First Amendment to the U.S. Constitution, and the laws are rarely enforced. There are no criminal defamation or insult laws at the federal level. However, on the state level, 23 states and two territories have criminal defamation laws on the books: Alabama, Florida, Idaho, Illinois, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Mississippi, Montana, Nevada, New Hampshire, New Mexico, North Carolina, North Dakota, Oklahoma, South Carolina, Texas, Utah, Virginia, Wisconsin, Puerto Rico and Virgin Islands. In addition, Iowa criminalizes defamation through case law without statutorily defining it as a crime.


title: Defamation

text: "Noonan v. Staples" is sometimes cited as precedent that truth is not always a defence to libel in the U.S., but the case is actually not valid precedent on that issue because Staples did not argue First Amendment protection, which is one theory for truth as complete defence, for its statements. The court assumed in this case that the Massachusetts law was constitutional under the First Amendment without it being argued by the parties.


title: Defamation

text: In March 2016, a civil action for defamation led to imposition of a four-year prison sentence on a newspaper publisher.


title: Defamation

text: The rise of the internet as a medium for publication and the expression of ideas, including the emergence of social media platforms transcending national boundaries, has proven challenging to reconcile with traditional notions of defamation law. Questions of jurisdiction and conflicting limitation periods in trans-border online defamation cases, liability for hyperlinks to defamatory content, filing lawsuits against anonymous parties, and the liability of internet service providers and intermediaries make online defamation a uniquely complicated area of law. As a result, courts and legislatures in different jurisdictions have approached online defamation in a variety of different and conflicting ways.


title: Defamation

text: In South Korea, the rise of the internet has led to the emergence of cyber defamation law as a distinct and polarising field of law. Some Korean celebrities who suffered from severe depression linked malicious online comments later committed suicide, which served in part to stimulate moves to strengthen cyber defamation law. The vast majority of cyber defamation police reports in South Korea arise from online games, and, in 2015 alone, South Korean law enforcement received and investigated over 8,000 reports of cyber defamation; over half of these cases involve "League of Legends", where players head to police stations as a retaliation after being verbally abused by teammates or opponents. There are even 'settlement fee hunters', where players enter games and grief with intention of being insulted by other players. In some cases, such settlement fee hunters file police reports against over 50 other individuals at once. Most of the victims of settlement fee hunters are teenagers, since many parents are willing to pay settlement fees ranging from 300,000 to 2,000,000 KRW (US$300–2000) to avoid their children having to go to trial and risk gaining criminal records.


title: Defamation

text: In 2012, the Philippines enacted Republic Act 10175, titled "Cybercrime Prevention Act of 2012". Essentially, this Act provides that libel is criminally punishable and describes it as: "Libel – the unlawful or prohibited act as defined in Article 355 of the Revised Penal Code, as amended, committed through a computer system or any other similar means which may be devised in the future." Professor Harry Roque of the University of the Philippines has written that under this law, electronic libel is punished with imprisonment from six years and one day to up to twelve years. , five petitions claiming the law to be unconstitutional had been filed with the Philippine Supreme Court, one by Senator Teofisto Guingona III. The petitions all claim that the law infringes on freedom of expression, due process, equal protection and privacy of communication.


title: Defamation

text: Australia's first Twitter defamation case to go to trial is believed to be "Mickle v Farley". The defendant, former Orange High School student Andrew Farley was ordered to pay $105,000 to a teacher for writing defamatory remarks about her on the social media platform. A more recent case in defamation law was "Hockey v Fairfax Media Publications Pty Limited" [2015], heard in the Federal Court of Australia. This judgment was significant as it demonstrated that tweets, consisting of even as little as three words, can be defamatory, as was held in this case.


title: Defamation

text: Regarding defamation on the internet, in 2011 the Supreme Court of Canada held that a person who posts hyperlinks on a website which lead to another site with defamatory content is not publishing that defamatory material for the purposes of libel and defamation law.


title: Defamation

text: In Singapore, Division 2 of Part 3 of the Protection from Harassment Act 2014 provides for individuals who have been affected by false statements online to seek a variety of court orders under the tort of harassment that are not available under the pre-internet tort of defamation:


title: Defamation

text: This is distinct from and does not affect plaintiffs right of action under the common law torts of libel and slander as modified by the Defamation Act 1957. The Protection of Harassment Act 2014, which provides for criminal penalties in addition to civil remedies, is specifically designed to address a narrower scope of conduct in order to avoid outlawing an overly broad range of speech, and is confined to addressing speech that causes "harassment, alarm, or distress".


title: Defamation

text: Beyond simply addressing novel instances of defamation enabled by the rise of the internet, courts around the world have also had to deal with complex jurisdictional issues regarding trans-border online defamation. On 10 December 2002, the High Court of Australia responded to this emerging phenomenon by vastly expanding the international jurisdiction of Australian courts in its judgment in "Dow Jones v Gutnick". The judgment established that internet-published foreign publications that defamed an Australian in their Australian reputation could be held accountable under Australian defamation law. The case gained worldwide attention and is often said, inaccurately, to be the first of its kind. A similar case that predates "Dow Jones v Gutnick" is "Berezovsky v Forbes" in England. This decision was criticised in the United States, though it mirrors similar decisions in many other jurisdictions such as England, Scotland, France, Canada and Italy.


title: Defamation

text: In response to the expansion of other jurisdictions' attempts to enforce judgements in cases of trans-border defamation and to a rise in domestic strategic lawsuits against public participation (SLAPPs) following the rise of the internet, the Federal and many state governments in America have adopted statutes limiting the enforceability of offshore defamation judgments and expediting the dismissal of defamation claims. American writers and publishers are shielded from the enforcement of offshore libel judgments not compliant under the SPEECH Act, which was passed by the 111th United States Congress and signed into law by President Barack Obama in 2010. It is based on the New York State 2008 Libel Terrorism Protection Act (also known as "Rachel's Law", after Rachel Ehrenfeld who initiated the state and federal laws). Both the New York state law and the federal law were passed unanimously.


title: Defamation

text: The "Catholic Encyclopedia" defines slander as "the attributing to another of a fault of which one knows him to be innocent".


title: Defamation

text: The effects of it are "a twofold malice, that which grows out of damage unjustly done to our neighbor's good name and that of lying as well. Theologians say that this latter guilt considered in itself, in so far as it is an offence against veracity, may not be grievous, but that nevertheless it will frequently be advisable to mention it in confession, in order that the extent and method of reparation may be settled."


title: Defamation

text: Defamation in said to be a violation of the eighth commandment: "Thou shalt not bear false witness against thy neighbor." Joseph Deharbe lists two possible reasons when one is "allowed, and even bound, to reveal them, 1. When it is for the good of the guilty person; or 2. When it is necessary for preventing a greater evil."


title: Defamation

text: In the Epistle of James there are two references to defamation: "If any man offend not in word, the same is a perfect man"; and again, "The tongue is indeed a little member, and boasts great things. Behold how small a fire what a great wood it kindles." ( 3:2,5)


title: Defamation

text: Based on these verse, the Roman Catechism makes the following statement: "from these words of St. James we learn two salutary truths: the one, that the vice of the tongue is of great extent, a truth which derives additional confirmation from these words of the prophet, 'Every man is a liar' (Ps. 115:11); whence this moral disease would seem to be almost the only one which extends to all mankind: the other, that the tongue is the source of innumerable evils."


title: Defamation

text: Jean-Baptiste Massillon gives a lengthy sermon on defamation in which he states, "the tongue of the slanderer is a devouring fire, which tarnishes whatever it touches; which exercises its fury on the good grain, equally as on the chaff; on the profane, as on the sacred; which wherever it passes, leaves only desolation and ruin; digs even into the bowels of the earth, and fixes itself on things the most hidden; turns into vile ashes, what, only a moment before, had appeared to us so precious and brilliant."


title: Generative adversarial network

text: A generative adversarial network (GAN) is a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in June 2014. Two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss.


title: Generative adversarial network

text: Given a training set, this technique learns to generate new data with the same statistics as the training set. For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning, GANs have also proved useful for semi-supervised learning, fully supervised learning, and reinforcement learning.


title: Generative adversarial network

text: The core idea of a GAN is based on the "indirect" training through the discriminator, another neural network that can tell how "realistic" the input seems, which itself is also being updated dynamically. This means that the generator is not trained to minimize the distance to a specific image, but rather to fool the discriminator. This enables the model to learn in an unsupervised manner.


title: Generative adversarial network

text: GANs are similar to mimicry in evolutionary biology, with an evolutionary arms race between both networks.


title: Generative adversarial network

text: The generator's strategy set is formula_2, the set of all probability measures formula_3 on formula_4.


title: Generative adversarial network

text: The discriminator's strategy set is the set of Markov kernels formula_5, where formula_6 is the set of probability measures on formula_7.


title: Generative adversarial network

text: The generator's task is to approach formula_9, that is, to match its own output distribution as closely as possible to the reference distribution. The discriminator's task is to output a value close to 1 when the input appears to be from the reference distribution, and to output a value close to 0 when the input looks like it came from the generator distribution.


title: Generative adversarial network

text: The "generative" network generates candidates while the "discriminative" network evaluates them. The contest operates in terms of data distributions. Typically, the generative network learns to map from a latent space to a data distribution of interest, while the discriminative network distinguishes candidates produced by the generator from the true data distribution. The generative network's training objective is to increase the error rate of the discriminative network (i.e., "fool" the discriminator network by producing novel candidates that the discriminator thinks are not synthesized (are part of the true data distribution)).


title: Generative adversarial network

text: A known dataset serves as the initial training data for the discriminator. Training involves presenting it with samples from the training dataset until it achieves acceptable accuracy. The generator is trained based on whether it succeeds in fooling the discriminator. Typically, the generator is seeded with randomized input that is sampled from a predefined latent space (e.g. a multivariate normal distribution). Thereafter, candidates synthesized by the generator are evaluated by the discriminator. Independent backpropagation procedures are applied to both networks so that the generator produces better samples, while the discriminator becomes more skilled at flagging synthetic samples. When used for image generation, the generator is typically a deconvolutional neural network, and the discriminator is a convolutional neural network.


title: Generative adversarial network

text: GANs are implicit generative models, which means that they do not explicitly model the likelihood function nor provide a means for finding the latent variable corresponding to a given sample, unlike alternatives such as flow-based generative model.


title: Generative adversarial network

text: Compared to fully visible belief networks such as WaveNet and PixelRNN and autoregressive models in general, GANs can generate one complete sample in one pass, rather than multiple passes through the network.


title: Generative adversarial network

text: Compared to Boltzmann machines and nonlinear ICA, there is no restriction on the type of function used by the network.


title: Generative adversarial network

text: Since neural networks are universal approximators, GANs are asymptotically consistent. Variational autoencoders might be universal approximators, but it is not proven as of 2017.


title: Generative adversarial network

text: In modern probability theory based on measure theory, a probability space also needs to be equipped with a σ-algebra. As a result, a more rigorous definition of the GAN game would make the following changes:Each probability space formula_10 defines a GAN game.


title: Generative adversarial network

text: The generator's strategy set is formula_11, the set of all probability measures formula_3 on the measure-space formula_13.


title: Generative adversarial network

text: The discriminator's strategy set is the set of Markov kernels formula_14, where formula_15 is the Borel σ-algebra on formula_7.Since issues of measurability never arise in practice, these will not concern us further.


title: Generative adversarial network

text: In the most generic version of the GAN game described above, the strategy set for the discriminator contains all Markov kernels formula_17, and the strategy set for the generator contains arbitrary probability distributions formula_3 on formula_4.


title: Generative adversarial network

text: However, as shown below, the optimal discriminator strategy against any formula_3 is deterministic, so there is no loss of generality in restricting the discriminator's strategies to deterministic functions formula_21. In most applications, formula_22 is a deep neural network function.


title: Generative adversarial network

text: As for the generator, while formula_3 could theoretically be any computable probability distribution, in practice, it is usually implemented as a pushforward: formula_24. That is, start with a random variable formula_25, where formula_26 is a probability distribution that is easy to compute (such as the uniform distribution, or the Gaussian distribution), then define a function formula_27. Then the distribution formula_3 is the distribution of formula_29.


title: Generative adversarial network

text: Consequently, the generator's strategy is usually defined as just formula_30, leaving formula_25 implicit. In this formalism, the GAN game objective isformula_32


title: Generative adversarial network

text: The GAN architecture has two main components. One is casting optimization into a game, of form formula_33, which is different from the usual kind of optimization, of form formula_34. The other is the decomposition of formula_35 into formula_36, which can be understood as a reparametrization trick.


title: Generative adversarial network

text: To see its significance, one must compare GAN with previous methods for learning generative models, which were plagued with "intractable probabilistic computations that arise in maximum likelihood estimation and related strategies".


title: Generative adversarial network

text: At the same time, Kingma and Welling and Rezende et al. developed the same idea of reparametrization into a general stochastic backpropagation method. Among its first applications was the variational autoencoder.


title: Generative adversarial network

text: In the original paper, as well as most subsequent papers, it is usually assumed that the generator "moves first", and the discriminator "moves second", thus giving the following minimax game:formula_37


title: Generative adversarial network

text: If both the generator's and the discriminator's strategy sets are spanned by a finite number of strategies, then by the minimax theorem,formula_38that is, the move order does not matter.


title: Generative adversarial network

text: However, since the strategy sets are both not finitely spanned, the minimax theorem does not apply, and the idea of an "equilibrium" becomes delicate. To wit, there are the following different concepts of equilibrium:


title: Generative adversarial network

text: For general games, these equilibria do not have to agree, or even to exist. For the original GAN game, these equilibria all exist, and are all equal. However, for more general GAN games, these do not necessarily exist, or agree.


title: Generative adversarial network

text: where the derivative is the Radon–Nikodym derivative, and formula_43 is the Jensen–Shannon divergence.


title: Generative adversarial network

text: and similarly for the other term. Therefore, the optimal reply can be deterministic, i.e. formula_44 for some function formula_45, in which case


title: Generative adversarial network

text: To define suitable density functions, we define a base measure formula_47, which allows us to take the Radon–Nikodym derivatives


title: Generative adversarial network

text: The integrand is just the negative cross-entropy between two Bernoulli random variables with parameters formula_51 and formula_52. We can write this as formula_53, where formula_54 is the binary entropy function, so


title: Generative adversarial network

text: Interpretation: For any fixed generator strategy formula_3, the optimal discriminator keeps track of the likelihood ratio between the reference distribution and the generator distribution:formula_59where formula_60 is the logistic function.


title: Generative adversarial network

text: In particular, if the prior probability for an image formula_61 to come from the reference distribution is equal to formula_62, then formula_52 is just the posterior probability that formula_61 came from the reference distribution:formula_65


title: Generative adversarial network

text: While the GAN game has a unique global equilibrium point when both the generator and discriminator have access to their entire strategy sets, the equilibrium is no longer guaranteed when they have a restricted strategy set.


title: Generative adversarial network

text: In practice, the generator has access only to measures of form formula_73, where formula_74 is a function computed by a neural network with parameters formula_75, and formula_26 is an easily sampled distribution, such as the uniform or normal distribution. Similarly, the discriminator has access only to functions of form formula_77, a function computed by a neural network with parameters formula_78. These restricted strategy sets take up a "vanishingly small proportion" of their entire strategy sets.


title: Generative adversarial network

text: Further, even if an equilibrium still exists, it can only be found by searching in the high-dimensional space of all possible neural network functions. The standard strategy of using gradient descent to find the equilibrium often does not work for GAN, and often the game "collapses" into one of several failure modes.


title: Generative adversarial network

text: GANs often suffer from mode collapse where they fail to generalize properly, missing entire modes from the input data. For example, a GAN trained on the MNIST dataset containing many samples of each digit might only generate pictures of digit 0. This was named in the first paper as the "Helvetica scenario".


title: Generative adversarial network

text: One way this can happen is if the generator learns too fast compared to the discriminator. If the discriminator formula_22 is held constant, then the optimal generator would only output elements of formula_80. So for example, if during GAN training for generating MNIST dataset, for a few epochs, the discriminator somehow prefers the digit 0 slightly more than other digits, the generator may seize the opportunity to generate only digit 0, then be unable to escape the local minimum after the discriminator improves.


title: Generative adversarial network

text: Some researchers perceive the root problem to be a weak discriminative network that fails to notice the pattern of omission, while others assign blame to a bad choice of objective function. Many solutions have been proposed, but it is still an open problem.


title: Generative adversarial network

text: Even the state-of-the-art architecture, BigGAN (2019), could not avoid mode collapse. The authors resorted to "allowing collapse to occur at the later stages of training, by which time a model is sufficiently trained to achieve good results".


title: Generative adversarial network

text: The two time-scale update rule (TTUR) is proposed to make GAN convergence more stable by making the learning rate of the generator lower than that of the discriminator. The authors argued that the generator should move slower than the discriminator, so that it does not "drive the discriminator steadily into new regions without capturing its gathered information".


title: Generative adversarial network

text: They proved that a general class of games that included the GAN game, when trained under TTUR, "converges under mild assumptions to a stationary local Nash equilibrium".


title: Generative adversarial network

text: They also proposed using the Adam stochastic optimization to avoid mode collapse, as well as the Fréchet inception distance for evaluating GAN performances.


title: Generative adversarial network

text: Conversely, if the discriminator learns too fast compared to the generator, then the discriminator could almost perfectly distinguish formula_81. In such case, the generator formula_74 could be stuck with a very high loss no matter which direction it changes its formula_75, meaning that the gradient formula_84 would be close to zero. In such case, the generator cannot learn, a case of the vanishing gradient problem.


title: Generative adversarial network

text: Intuitively speaking, the discriminator is too good, and since the generator cannot take any small step (only small steps are considered in gradient descent) to improve its payoff, it does not even try.


title: Generative adversarial network

text: GANs are usually evaluated by Inception score (IS), which measures how varied the generator's outputs are (as classified by a image classifier, usually Inception-v3), or Fréchet inception distance (FID), which measures how similar the generator's outputs are to a reference set (as classified by a learned image featurizer, such as Inception-v3 without its final layer). Many papers that propose new GAN architectures for image generation report how their architectures break the state of the art on FID or IS.


title: Generative adversarial network

text: Another evaluation method is the Learned Perceptual Image Patch Similarity (LPIPS), which starts with a learned image featurizer formula_85, and finetunes it by supervised learning on a set of formula_86, where formula_61 is an image, formula_88 is a perturbed version of it, and formula_89 is how much they differ, as reported by human subjects. The model is finetuned so that it can approximate formula_90. This finetuned model is then used to define formula_91.


title: Generative adversarial network

text: Conditional GANs are similar to standard GANs except they allow the model to conditionally generate samples based on additional information. For example, if we want to generate a cat face given a dog picture, we could use a conditional GAN


title: Generative adversarial network

text: The generator in a GAN game generates formula_3, a probability distribution on the probability space formula_4. This leads to the idea of a conditional GAN, where instead of generating one probability distribution on formula_4, the generator generates a different probability distribution formula_95 on formula_4, for each given class label formula_97.


title: Generative adversarial network

text: For example, for generating images that look like ImageNet, the generator should be able to generate a picture of cat when given the class label "cat".


title: Generative adversarial network

text: In the original paper, the authors noted that GAN can be trivially extended to conditional GAN by providing the labels to both the generator and the discriminator.


title: Generative adversarial network

text: Concretely, the conditional GAN game is just the GAN game with class labels provided:formula_98where formula_99 is a probability distribution over classes, formula_100 is the probability distribution of real images of class formula_97, and formula_95 the probability distribution of images generated by the generator when given class label formula_97.


title: Generative adversarial network

text: The GAN game is a general framework and can be run with any reasonable parametrization of the generator formula_30 and discriminator formula_22. In the original paper, the authors demonstrated it using multilayer perceptron networks and convolutional neural networks. Many alternative architectures have been tried.


title: Generative adversarial network

text: Deep convolutional GAN (DCGAN): For both generator and discriminator, uses only deep networks consisting entirely of convolution-deconvolution layers, that is, fully convolutional networks.


title: Generative adversarial network

text: Self-attention GAN (SAGAN): Starts with the DCGAN, then adds residually-connected standard self-attention modules to the generator and discriminator.


title: Generative adversarial network

text: Transformer GAN (TransGAN): Uses the pure transformer architecture for both the generator and discriminator, entirely devoid of convolution-deconvolution layers.


title: Generative adversarial network

text: Flow-GAN: Uses flow-based generative model for the generator, allowing efficient computation of the likelihood function.


title: Generative adversarial network

text: Many GAN variants are merely obtained by changing the loss functions for the generator and discriminator.


title: Generative adversarial network

text: This objective for generator was recommended in the original paper for faster convergence.formula_107The effect of using this objective is analyzed in Section 2.2.2 of.


title: Generative adversarial network

text: formula_108where formula_60 is the logistic function. When the discriminator is optimal, the generator gradient is the same as in maximum likelihood estimation, even though GAN cannot perform maximum likelihood estimation "itself".


title: Generative adversarial network

text: Hinge loss GAN:formula_110formula_111Least squares GAN:formula_112formula_113where formula_114 are parameters to be chosen. The authors recommended formula_115.


title: Generative adversarial network

text: One of its purposes is to solve the problem of mode collapse (see above). The authors claim "In no experiment did we see evidence of mode collapse for the WGAN algorithm".


title: Generative adversarial network

text: In conditional GAN, the generator receives both a noise vector formula_120 and a label formula_97, and produces an image formula_122. The discriminator receives image-label pairs formula_123, and computes formula_124.


title: Generative adversarial network

text: The idea of InfoGAN is to decree that every latent vector in the latent space can be decomposed as formula_125: an incompressible noise part formula_120, and an informative label part formula_97, and encourage the generator to comply with the decree, by encouraging it to maximize formula_128, the mutual information between formula_97 and formula_122, while making no demands on the mutual information formula_120 between formula_122.


title: Generative adversarial network

text: Unfortunately, formula_128 is intractable in general, The key idea of InfoGAN is Variational Mutual Information Maximization: indirectly maximize it by maximizing a lower boundformula_134where formula_135 ranges over all Markov kernels of type formula_136.


title: Generative adversarial network

text: There are 3 players in 2 teams: generator, Q, and discriminator. The generator and Q are on one team, and the discriminator on the other team.


title: Generative adversarial network

text: The objective function isformula_140where formula_141 is the original GAN game objective, and formula_142


title: Generative adversarial network

text: The standard GAN generator is a function of type formula_144, that is, it is a mapping from a latent space formula_145 to the image space formula_146. This can be understood as a "decoding" process, whereby every latent vector formula_147 is a code for an image formula_148, and the generator performs the decoding. This naturally leads to the idea of training another network that performs "encoding", creating an autoencoder out of the encoder-generator pair.


title: Generative adversarial network

text: Already in the original paper, the authors noted that "Learned approximate inference can be performed by training an auxiliary network to predict formula_120 given formula_61". The bidirectional GAN architecture performs exactly this.


title: Generative adversarial network

text: There are 3 players in 2 teams: generator, encoder, and discriminator. The generator and encoder are on one team, and the discriminator on the other team.


title: Generative adversarial network

text: The generator's strategies are functions formula_153, and the encoder's strategies are functions formula_154. The discriminator's strategies are functions formula_155.


title: Generative adversarial network

text: Generator-encoder team aims to minimize the objective, and discriminator aims to maximize it:formula_157 In the paper, they gave a more abstract definition of the objective as:formula_158where formula_159 is the probability distribution on formula_160 obtained by pushing formula_161 forward via formula_162, and formula_163 is the probability distribution on formula_160 obtained by pushing formula_26 forward via formula_166.


title: Generative adversarial network

text: Applications of bidirectional models include semi-supervised learning, interpretable machine learning, and neural machine translation.


title: Generative adversarial network

text: Variational autoencoders (VAEs) are unsupervised models that learn a probabilistic latent representation of their inputs. VAEs consist of an encoder and decoder. The encoder maps high dimensional data into a low dimensional space where it can be represented using a simple parametric function. The decoder then reconstructs the original data back into its high dimensional space. The decoder uses variational inference to approximate the posterior over the latent variables.


title: Generative adversarial network

text: CycleGAN is an architecture for performing translations between two domains, such as between photos of horses and photos of zebras, or photos of night cities and photos of day cities.


title: Generative adversarial network

text: The CycleGAN game is defined as follows:There are two probability spaces formula_167, corresponding to the two domains needed for translations fore-and-back.


title: Generative adversarial network

text: where formula_171 is a positive adjustable parameter, formula_172 is the GAN game objective, and formula_173 is the "cycle consistency loss":formula_174The generators aim to minimize the objective, and the discriminators aim to maximize it:formula_175 Unlike previous work like pix2pix, which requires paired training data, cycleGAN requires no paired data. For example, to train a pix2pix model to turn a summer scenery photo to winter scenery photo and back, the dataset must contain pairs of the same place in summer and winter, shot at the same angle; cycleGAN would only need a set of summer scenery photos, and an unrelated set of winter scenery photos.


title: Generative adversarial network

text: The BigGAN is essentially a self-attention GAN trained on a large scale (up to 80 million parameters) to generate large images of ImageNet (up to 512 x 512 resolution), with numerous engineering tricks to make it converge.


title: Generative adversarial network

text: When there is insufficient training data, the reference distribution formula_176 cannot be well-approximated by the empirical distribution given by the training dataset. In such cases, data augmentation can be applied, to allow training GAN on smaller datasets. Naïve data augmentation, however, brings its problems.


title: Generative adversarial network

text: Consider the original GAN game, slightly reformulated as follows:formula_106Now we use data augmentation by randomly sampling semantic-preserving transforms formula_178 and applying them to the dataset, to obtain the reformulated GAN game:formula_179This is equivalent to a GAN game with a different distribution formula_180, sampled by formula_181, with formula_182. For example, if formula_176 is the distribution of images in ImageNet, and formula_184 samples identity-transform with probability 0.5, and horizontal-reflection with probability 0.5, then formula_180 is the distribution of images in ImageNet and horizontally-reflected ImageNet, combined.


title: Generative adversarial network

text: The result of such training would be a generator that mimics formula_180. For example, it would generate images that look like they are randomly cropped, if the data augmentation uses random cropping.


title: Generative adversarial network

text: The solution is to apply data augmentation to both generated and real images:formula_187The authors demonstrated high-quality generation using just 100-picture-large datasets.


title: Generative adversarial network

text: The StyleGAN-2-ADA paper points out a further point on data augmentation: it must be "invertible". Continue with the example of generating ImageNet pictures. If the data augmentation is "randomly rotate the picture by 0, 90, 180, 270 degrees with "equal" probability", then there is no way for the generator to know which is the true orientation: Consider two generators formula_188, such that for any latent formula_120, the generated image formula_29 is a 90-degree rotation of formula_191. They would have exactly the same expected loss, and so neither is preferred over the other.


title: Generative adversarial network

text: The solution is to only use invertible data augmentation: instead of "randomly rotate the picture by 0, 90, 180, 270 degrees with "equal" probability", use "randomly rotate the picture by 90, 180, 270 degrees with 0.1 probability, and keep the picture as it is with 0.7 probability". This way, the generator is still rewarded to keep images oriented the same way as un-augmented ImageNet pictures.


title: Generative adversarial network

text: Abstractly, the effect of randomly sampling transformations formula_178 from the distribution formula_184 is to define a Markov kernel formula_194. Then, the data-augmented GAN game pushes the generator to find some formula_195, such that formula_196where formula_197 is the Markov kernel convolution.


title: Generative adversarial network

text: A data-augmentation method is defined to be "invertible" if its Markov kernel formula_198 satisfiesformula_199Immediately by definition, we see that composing multiple invertible data-augmentation methods results in yet another invertible method. Also by definition, if the data-augmentation method is invertible, then using it in a GAN game does not change the optimal strategy formula_200 for the generator, which is still formula_176.


title: Generative adversarial network

text: For example, if formula_203 is the set of four images of an arrow, pointing in 4 directions, and the data augmentation is "randomly rotate the picture by 90, 180, 270 degrees with probability formula_204, and keep the picture as it is with probability formula_205", then the Markov kernel formula_198 can be represented as a stochastic matrix:formula_207 and formula_198 is an invertible kernel iff formula_209 is an invertible matrix, that is, formula_210.


title: Generative adversarial network

text: For example, if formula_213 is the space of 256x256 images, and the data-augmentation method is "generate a gaussian noise formula_214, then add formula_215 to the image", then formula_198 is just convolution by the density function of formula_217. This is invertible, because convolution by a gaussian is just convolution by the heat kernel, so given any formula_218, the convolved distribution formula_219 can be obtained by heating up formula_220 precisely according to formula_221, then wait for time formula_222. With that, we can recover formula_221 by running the heat equation "backwards in time" for formula_222.


title: Generative adversarial network

text: SinGAN pushes data augmentation to the limit, by using only a single image as training data and performing data augmentation on it. The GAN architecture is adapted to this training method by using a multi-scale pipeline.


title: Generative adversarial network

text: The generator formula_30 is decomposed into a pyramid of generators formula_226, with the lowest one generating the image formula_227 at the lowest resolution, then the generated image is scaled up to formula_228, and fed to the next level to generate an image formula_229 at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.


title: Generative adversarial network

text: Progressive GAN is a method for training GAN for large-scale image generation stably, by growing a GAN generator from small to large scale in a pyramidal fashion. Like SinGAN, it decomposes the generator asformula_226, and the discriminator as formula_231.


title: Generative adversarial network

text: During training, at first only formula_232 are used in a GAN game to generate 4x4 images. Then formula_233 are added to reach the second stage of GAN game, to generate 8x8 images, and so on, until we reach a GAN game to generate 1024x1024 images.


title: Generative adversarial network

text: To avoid shock between stages of the GAN game, each new layer is "blended in" (Figure 2 of the paper). For example, this is how the second stage GAN game starts:


title: Generative adversarial network

text: The key architectural choice of StyleGAN-1 is a progressive growth mechanism, similar to Progressive GAN. Each generated image starts as a constant formula_238 array, and repeatedly passed through style blocks. Each style block applies a "style latent vector" via affine transform ("adaptive instance normalization"), similar to how neural style transfer uses Gramian matrix. It then adds noise, and normalize (subtract the mean, then divide by the variance).


title: Generative adversarial network

text: At training time, usually only one style latent vector is used per image generated, but sometimes two ("mixing regularization") in order to encourage each style block to independently perform its stylization without expecting help from other style blocks (since they might receive an entirely different style latent vector).


title: Generative adversarial network

text: After training, multiple style latent vectors can be fed into each style block. Those fed to the lower layers control the large-scale styles, and those fed to the higher layers control the fine-detail styles.


title: Generative adversarial network

text: Style-mixing between two images formula_239 can be performed as well. First, run a gradient descent to find formula_240 such that formula_241. This is called "projecting an image back to style latent space". Then, formula_120 can be fed to the lower style blocks, and formula_243 to the higher style blocks, to generate a composite image that has the large-scale style of formula_61, and the fine-detail style of formula_88. Multiple images can also be composed this way.


title: Generative adversarial network

text: StyleGAN-2 improves upon StyleGAN-1, by using the style latent vector to transform the convolution layer's weights instead, thus solving the "blob" problem.


title: Generative adversarial network

text: This was updated by the StyleGAN-2-ADA ("ADA" stands for "adaptive"), which uses invertible data augmentation as described above. It also tunes the amount of data augmentation applied by starting at zero, and gradually increasing it until an "overfitting heuristic" reaches a target level, thus the name "adaptive".


title: Generative adversarial network

text: StyleGAN-3 improves upon StyleGAN-2 by solving the "texture sticking" problem, which can be seen in the official videos. They analyzed the problem by the Nyquist–Shannon sampling theorem, and argued that the layers in the generator learned to exploit the high-frequency signal in the pixels they operate upon.


title: Generative adversarial network

text: To solve this, they proposed imposing strict lowpass filters between each generator's layers, so that the generator is forced to operate on the pixels in a way faithful to the continuous signals they represent, rather than operate on them as merely discrete signals. They further imposed rotational and translational invariance by using more signal filters. The resulting StyleGAN-3 is able to solve the texture sticking problem, as well as generating images that rotate and translate smoothly.


title: Generative adversarial network

text: GANs can be used to generate art; "The Verge" wrote in March 2019 that "The images created by GANs have become the defining look of contemporary AI art." GANs can also be used to inpaint photographs or create photos of imaginary fashion models, with no need to hire a model, photographer or makeup artist, or pay for a studio and transportation. GANs have also been used for virtual shadow generation.


title: Generative adversarial network

text: In 2020, Artbreeder was used to create the main antagonist in the sequel to the psychological web horror series "Ben Drowned". The author would later go on to praise GAN applications for their ability to help generate assets for independent artists who are short on budget and manpower.


title: Generative adversarial network

text: GANs can improve astronomical images and simulate gravitational lensing for dark matter research. They were used in 2019 to successfully model the distribution of dark matter in a particular direction in space and to predict the gravitational lensing that will occur.


title: Generative adversarial network

text: GANs have been proposed as a fast and accurate way of modeling high energy jet formation and modeling showers through calorimeters of high-energy physics experiments. GANs have also been trained to accurately approximate bottlenecks in computationally expensive simulations of particle physics experiments. Applications in the context of present and proposed CERN experiments have demonstrated the potential of these methods for accelerating simulation and/or improving simulation fidelity.


title: Generative adversarial network

text: In 2018, GANs reached the video game modding community, as a method of up-scaling low-resolution 2D textures in old video games by recreating them in 4k or higher resolutions via image training, and then down-sampling them to fit the game's native resolution (with results resembling the supersampling method of anti-aliasing). With proper training, GANs provide a clearer and sharper 2D texture image magnitudes higher in quality than the original, while fully retaining the original's level of details, colors, etc. Known examples of extensive GAN usage include "Final Fantasy VIII", "Final Fantasy IX", "Resident Evil REmake" HD Remaster, and "Max Payne".


title: Generative adversarial network

text: Concerns have been raised about the potential use of GAN-based human image synthesis for sinister purposes, e.g., to produce fake, possibly incriminating, photographs and videos.


title: Generative adversarial network

text: GANs can be used to generate unique, realistic profile photos of people who do not exist, in order to automate creation of fake social media profiles.


title: Generative adversarial network

text: In 2019 the state of California considered and passed on October 3, 2019, the bill AB-602, which bans the use of human image synthesis technologies to make fake pornography without the consent of the people depicted, and bill AB-730, which prohibits distribution of manipulated videos of a political candidate within 60 days of an election. Both bills were authored by Assembly member Marc Berman and signed by Governor Gavin Newsom. The laws went into effect in 2020.


title: Generative adversarial network

text: DARPA's Media Forensics program studies ways to counteract fake media, including fake media produced using GANs.


title: Generative adversarial network

text: State-of-art transfer learning research use GANs to enforce the alignment of the latent feature space, such as in deep reinforcement learning. This works by feeding the embeddings of the source and target task to the discriminator which tries to guess the context. The resulting loss is then (inversely) backpropagated through the encoder.


title: Generative adversarial network

text: GAN can be used to detect glaucomatous images helping the early diagnosis which is essential to avoid partial or total loss


title: Generative adversarial network

text: GANs that produce photorealistic images can be used to visualize interior design, industrial design, shoes, bags, and clothing items or items for computer games' scenes. Such networks were reported to be used by Facebook.


title: Generative adversarial network

text: GANs can reconstruct 3D models of objects from images, generate novel objects as 3D point clouds, and model patterns of motion in video.


title: Generative adversarial network

text: GANs can be used to age face photographs to show how an individual's appearance might change with age.


title: Generative adversarial network

text: GANs can also be used to inpaint missing features in maps, transfer map styles in cartography or augment street view imagery.


title: Generative adversarial network

text: A variation of the GANs is used in training a network to generate optimal control inputs to nonlinear dynamical systems. Where the discriminatory network is known as a critic that checks the optimality of the solution and the generative network is known as an Adaptive network that generates the optimal control. The critic and adaptive network train each other to approximate a nonlinear optimal control.


title: Generative adversarial network

text: A GAN model called Speech2Face can reconstruct an image of a person's face after listening to their voice.


title: Generative adversarial network

text: In 2016 GANs were used to generate new molecules for a variety of protein targets implicated in cancer, inflammation, and fibrosis. In 2019 GAN-generated molecules were validated experimentally all the way into mice.


title: Generative adversarial network

text: Whereas the majority of GAN applications are in image processing, the work has also been done with time-series data. For example, recurrent GANs (R-GANs) have been used to generate energy data for machine learning.


title: Generative adversarial network

text: The most direct inspiration for GANs was noise-contrastive estimation, which uses the same loss function as GANs and which Goodfellow studied during his PhD in 2010–2014.


title: Generative adversarial network

text: Other people had similar ideas but did not develop them similarly. An idea involving adversarial networks was published in a 2010 blog post by Olli Niemitalo. This idea was never implemented and did not involve stochasticity in the generator and thus was not a generative model. It is now known as a conditional GAN or cGAN. An idea similar to GANs was used to model animal behavior by Li, Gauci and Gross in 2013.


title: Generative adversarial network

text: Adversarial machine learning has other uses besides generative modeling and can be applied to models other than neural networks. In control theory, adversarial learning based on neural networks was used in 2006 to train robust controllers in a game theoretic sense, by alternating the iterations between a minimizer policy, the controller, and a maximizer policy, the disturbance.


title: Generative adversarial network

text: In 2017, a GAN was used for image enhancement focusing on realistic textures rather than pixel-accuracy, producing a higher image quality at high magnification. In 2017, the first faces were generated. These were exhibited in February 2018 at the Grand Palais. Faces generated by StyleGAN in 2019 drew comparisons with Deepfakes.


title: Generative adversarial network

text: Beginning in 2017, GAN technology began to make its presence felt in the fine arts arena with the appearance of a newly developed implementation which was said to have crossed the threshold of being able to generate unique and appealing abstract paintings, and thus dubbed a "CAN", for "creative adversarial network". A GAN system was used to create the 2018 painting "Edmond de Belamy," which sold for US$432,500. An early 2019 article by members of the original CAN team discussed further progress with that system, and gave consideration as well to the overall prospects for an AI-enabled art.


title: Generative adversarial network

text: In May 2019, researchers at Samsung demonstrated a GAN-based system that produces videos of a person speaking, given only a single photo of that person.


title: Generative adversarial network

text: In August 2019, a large dataset consisting of 12,197 MIDI songs each with paired lyrics and melody alignment was created for neural melody generation from lyrics using conditional GAN-LSTM (refer to sources at GitHub AI Melody Generation from Lyrics).


title: Generative adversarial network

text: In May 2020, Nvidia researchers taught an AI system (termed "GameGAN") to recreate the game of "Pac-Man" simply by watching it being played.


title: Zolpidem

text: Zolpidem, sold under the brand name Ambien, among others, is a medication primarily used for the short-term treatment of sleeping problems. Guidelines recommend that it be used only after cognitive behavioral therapy for insomnia and behavioral changes, such as sleep hygiene, have been tried. It decreases the time to sleep onset by about fifteen minutes and at larger doses helps people stay asleep longer. It is taken by mouth and is available in conventional tablets, sublingual tablets, or oral spray.


title: Zolpidem

text: Common side effects include daytime sleepiness, headache, nausea, and diarrhea. More severe side effects include memory problems and hallucinations. The previously recommended dose was decreased in 2013, by the US Food and Drug Administration (FDA), to the immediate-release 10mg for men, and 5mg for women, in an attempt to reduce next-day somnolence. Newer extended-release formulations include the 6.25mg for women, and 12.5mg or 6.25mg for men, which also cause next-day somnolence when used in higher doses. Additionally, driving the next morning is not recommended with either higher doses or the long-acting formulation. While flumazenil, a GABA–receptor antagonist, can reverse zolpidem's effects, usually supportive care is all that is recommended in overdose.


title: Zolpidem

text: Zolpidem is a nonbenzodiazepine which acts as a sedative and hypnotic. Zolpidem is a GABA receptor agonist of the imidazopyridine class. It works by increasing GABA effects in the central nervous system by binding to GABA receptors at the same location as benzodiazepines. It generally has a half-life of two to three hours. This, however, is increased in those with liver problems.


title: Zolpidem

text: Zolpidem was approved for medical use in the United States in 1992. It became available as a generic medication in 2007. Zolpidem is a Schedule IV controlled substance under the Controlled Substances Act of 1970 (CSA). More than ten million prescriptions are filled each year in the United States, making it one of the most commonly used treatments for sleeping problems. In 2020, it was the 47th most commonly prescribed medication in the United States, with more than 14million prescriptions.


title: Zolpidem

text: Zolpidem is labelled for short-term (usually about two to six weeks) treatment of insomnia at the lowest possible dose. It may be used for both improving sleep onset, sleep onset latency, and staying asleep.


title: Zolpidem

text: Guidelines from NICE, the European Sleep Research Society, and the American College of Physicians recommend medication for insomnia (including possibly zolpidem) only as a second line treatment after non-pharmacological treatment options have been tried (e.g. cognitive behavioral therapy for insomnia). This is based in part on a 2012 review which found that zolpidem's effectiveness is nearly as much due to psychological effects as to the medication itself.


title: Zolpidem

text: A lower-dose version (3.5mg for men and 1.75mg for women) is given as a tablet under the tongue and used for middle-of-the-night awakenings. It can be taken if there are at least 4 hours between the time of administration and when the person must be awake.


title: Zolpidem

text: Zolpidem should not be taken by people with obstructive sleep apnea, myasthenia gravis, severe liver disease, respiratory depression; or by children, or people with psychotic illnesses. It should not be taken by people who are or have been addicted to other substances.


title: Zolpidem

text: Use of zolpidem may impair driving skills with a resultant increased risk of road traffic accidents. This adverse effect is not unique to zolpidem, but also occurs with other hypnotic drugs. Caution should be exercised by motor vehicle drivers. In 2013, the FDA recommended the dose for women be reduced and that prescribers should consider lower doses for men due to impaired function the day after taking the drug.


title: Zolpidem

text: Zolpidem should not be prescribed to older people, who are more sensitive to the effects of hypnotics including zolpidem and are at an increased risk of falls and adverse cognitive effects, such as delirium and neurocognitive disorder.


title: Zolpidem

text: Zolpidem has not been assigned to a pregnancy category by the FDA. Animal studies have revealed evidence of incomplete ossification and increased intrauterine fetal death at doses greater than seven times the maximum recommended human dose or higher; however, teratogenicity was not observed at any dose level. There are no controlled data in human pregnancy. In one case report, zolpidem was found in cord blood at delivery. Zolpidem is recommended for use during pregnancy only when benefits outweigh risks.


title: Zolpidem

text: The most common adverse effects of short-term use include headache (reported by 7% of people in clinical trials), drowsiness (2%), dizziness (1%), and diarrhea (1%); the most common side effects of long-term use included


title: Zolpidem

text: Zolpidem increases risk of depression, falls and bone fracture, poor driving, suppressed respiration, and has been associated with an increased risk of death. Upper and lower respiratory infections are also common (experienced by between 1 and 10% of people).


title: Zolpidem

text: Residual 'hangover' effects, such as sleepiness and impaired psychomotor and cognitive function, may persist into the day following nighttime administration. Such effects may impair the ability of users to drive safely and increase risks of falls and hip fractures. Around 3% of people taking zolpidem are likely to break a bone as a result of a fall due to impaired coordination caused by the drug.


title: Zolpidem

text: Some users have reported unexplained sleepwalking while using zolpidem, as well as sleep driving, night eating syndrome while asleep, and performing other daily tasks while sleeping. Research by Australia's National Prescribing Service found these events occur mostly after the first dose taken, or within a few days of starting therapy. In February 2008, the Australian Therapeutic Goods Administration attached a boxed warning concerning this adverse effect.


title: Zolpidem

text: As zolpidem is associated with drug tolerance and substance dependence, its prescription guidelines are only for severe insomnia and short periods of use at the lowest effective dose. Tolerance to the effects of zolpidem can develop in some people in just a few weeks. Abrupt withdrawal may cause delirium, seizures, or other adverse effects, especially if used for prolonged periods and at high doses. When drug tolerance and physical dependence to zolpidem develop, treatment usually entails a gradual dose reduction over a period of months to minimize withdrawal symptoms, which can resemble those seen during benzodiazepine withdrawal. Failing that, an alternative method may be necessary for some people, such as a switch to a benzodiazepine equivalent dose of a longer-acting benzodiazepine drug, as for diazepam or chlordiazepoxide, followed by a gradual reduction in dose of the long-acting benzodiazepine. In people who are difficult to treat, an inpatient flumazenil administration allows for rapid competitive binding of flumazenil to GABA–receptor as an antagonist, thus stopping (and effectively detoxifying) zolpidem from being able to bind as an agonist on GABA–receptor; slowly drug dependence or addiction to zolpidem will wane.