DataHammer/scimrc huggingface dataset:
Question: What problem does the work tackle?
Evidence: Pre-trained models have demonstrated their effectiveness in many downstream natural language processing (NLP) tasks. The availability of multilingual pre-trained models enables zero-shot transfer of NLP tasks from high resource languages to low resource ones. However, recent research in improving pre-trained models focuses heavily on English. While it is possible to train the latest neural architectures for other languages from scratch, it is undesirable due to the required amount of compute. In this work, we tackle the problem of transferring an existing pre-trained model from English to other languages under a limited computational budget. With a single GPU, our approach can obtain a foreign BERT base model within a day and a foreign BERT large within two days. Furthermore, evaluating our models on six languages, we demonstrate that our models are better than multilingual BERT on two zero-shot tasks: natural language inference and dependency parsing.
In this work, we tackle the problem of transferring an existing pretrained model from English to other languages under a limited computational budget.
Answer: The problem of transferring an existing pretrained model from English to other languages under a limited computational budget.
Question: As an expert skier, what are the top resorts in the US to go skiing?
Answer: There are many ski resorts in the United States that offer challenging terrain for expert level skiers.  Som of the top resorts are: Big Sky, Jackson Hole, Pallisades, Crested Butte, Telluride, and Silverthorn
Question: On a visit to a movie theater, classify the likelihood of finding each of the following as either 'highly likely', 'likely', 'unlikely' or 'highly unlikely'. popcorn, M&Ms, sushi, salad, pasta.
Answer: It is highly likely that popcorn would be found at a movie theater.
It is highly likely that M&Ms would be found at a movie theater.
It is highly unlikely that sushi would be found at a movie theater.
It is highly unlikely that salad would be found at a movie theater.
It is highly unlikely that pasta would be found at a movie theater.
Question: Believe it or not, Jimi Hendrix only had one Top 40 hit. Which song was it?
Answer: "All Along the Watchtower"
Question: What is a phenotype?
Answer: In genetics and genomics, the phenotype  is the set of observable characteristics or traits of an organism. The term covers the organism's morphology (physical form and structure), its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior. An organism's phenotype results from two basic factors: the expression of an organism's genetic code (its genotype) and the influence of environmental factors. Both factors may interact, further affecting the phenotype. When two or more clearly different phenotypes exist in the same population of a species, the species is called polymorphic. A well-documented example of polymorphism is Labrador Retriever coloring; while the coat color depends on many genes, it is clearly seen in the environment as yellow, black, and brown. Richard Dawkins in 1978 and then again in his 1982 book The Extended Phenotype suggested that one can regard bird nests and other built structures such as caddisfly larva cases and beaver dams as "extended phenotypes".

Wilhelm Johannsen proposed the genotype–phenotype distinction in 1911 to make clear the difference between an organism's hereditary material and what that hereditary material produces. The distinction resembles that proposed by August Weismann (1834–1914), who distinguished between germ plasm (heredity) and somatic cells (the body). More recently, in The Selfish Gene (1976), Dawkins distinguished these concepts as replicators and vehicles.

The genotype–phenotype distinction should not be confused with Francis Crick's central dogma of molecular biology, a statement about the directionality of molecular sequential information flowing from DNA to protein, and not the reverse.
Question: How they demonstrate that language-neutral component is sufficiently general in terms of modeling semantics to allow high-accuracy word-alignment?
Evidence: Table TABREF15 shows that word-alignment based on mBERT representations surpasses the outputs of the standard FastAlign tool even if it was provided large parallel corpus. This suggests that word-level semantics are well captured by mBERT contextual embeddings. For this task, learning an explicit projection had a negligible effect on the performance.
Table TABREF15 shows that word-alignment based on mBERT representations surpasses the outputs of the standard FastAlign tool even if it was provided large parallel corpus. This suggests that word-level semantics are well captured by mBERT contextual embeddings. For this task, learning an explicit projection had a negligible effect on the performance.
Answer: The answers are shown as follows:
* explicit projection had a negligible effect on the performance
Question: What are some defining qualities of authoritarianism?
Evidence: Authoritarianism is a political system characterized by the rejection of political plurality, the use of strong central power to preserve the political status quo, and reductions in the rule of law, separation of powers, and democratic voting. Political scientists have created many typologies describing variations of authoritarian forms of government. Authoritarian regimes may be either autocratic or oligarchic and may be based upon the rule of a party or the military. States that have a blurred boundary between democracy and authoritarianism have some times been characterized as "hybrid democracies", "hybrid regimes" or "competitive authoritarian" states.

The political scientist Juan Linz, in an influential 1964 work, An Authoritarian Regime: Spain, defined authoritarianism as possessing four qualities:

Limited political pluralism, is realized with constraints on the legislature, political parties and interest groups.
Political legitimacy is based upon appeals to emotion and identification of the regime as a necessary evil to combat "easily recognizable societal problems, such as underdevelopment or insurgency."
Minimal political mobilization, and suppression of anti-regime activities.
Ill-defined executive powers, often vague and shifting extend the power of the executive.
Minimally defined, an authoritarian government lacks free and competitive direct elections to legislatures, free and competitive direct or indirect elections for executives, or both. Broadly defined, authoritarian states include countries that lack civil liberties such as freedom of religion, or countries in which the government and the opposition do not alternate in power at least once following free elections. Authoritarian states might contain nominally democratic institutions such as political parties, legislatures and elections which are managed to entrench authoritarian rule and can feature fraudulent, non-competitive elections. In contexts of democratic backsliding, scholars tend to identify authoritarian political leaders based on certain tactics, such as: politicizing independent institutions, spreading disinformation, aggrandizing executive power, quashing dissent, targeting vulnerable communities, stoking violence, and corrupting elections. Since 1946, the share of authoritarian states in the international political system increased until the mid-1970s but declined from then until the year 2000.
Answer: 1. Limited political pluralism or outright rejection of political pluralism.
2. Lack of civil liberties
3. Lack of free, fair and competitive elections
4. So-called democratic institutions corrupted by authoritarian rule
5. Use of election tactics such as spreading misinformation, politicizing independent institutions, quashing dissent, engaging in culture wars, targeting vulnerable communities, stoking violence, and aggrandizing executive power.
6. Use of a strong central power to preserve the political status quo at the cost of basic democratic ideals such as the rule of law, separation of powers, and voting rights.
Question: From the passage, extract the list of movies that Pedro Almodovar produced. Include the year and the name. Place them in a bullet list.
Evidence: Pedro Almodóvar Caballero (Spanish pronunciation: [ˈpeðɾo almoˈðoβaɾ kaβaˈʝeɾo]; born 25 September 1949) is a Spanish filmmaker. His films are marked by melodrama, irreverent humour, bold colour, glossy décor, quotations from popular culture, and complex narratives. Desire, passion, family, and identity are among Almodóvar's most prevalent subjects in his films. Acclaimed as one of the most internationally successful Spanish filmmakers, Almodóvar and his films have gained worldwide interest and developed a cult following.

Almodóvar's career came to during La Movida Madrileña, a cultural renaissance that followed after the end of Francoist Spain. His early films characterised the sense of sexual and political freedom of the period. In 1986, he established his own film production company, El Deseo, with his younger brother Agustín Almodóvar, who has been responsible for producing all of his films since Law of Desire (1987). His breakthrough film was Women on the Verge of a Nervous Breakdown (1988), which was nominated for the Academy Award for Best Foreign Language Film.

He achieved further success often collaborating with actors Antonio Banderas and Penélope Cruz. He directed Tie Me Up! Tie Me Down! (1989), High Heels (1991), and Live Flesh (1997). His next two films, All About My Mother (1999) and Talk to Her (2002), earned him an Academy Award each for Best International Feature Film and Best Original Screenplay, respectively. His later films include Volver (2006), Broken Embraces (2009), The Skin I Live In (2011), Julieta (2016), Pain and Glory (2019), and Parallel Mothers (2021).

Almodóvar has received numerous accolades including two Academy Awards, five BAFTA Awards, two Emmy Awards, two Golden Globe Awards, nine Goya Awards. He has also received the French Legion of Honour in 1997, the Gold Medal of Merit in the Fine Arts in 1999, and the European Film Academy Achievement in World Cinema Award in 2013 and was awarded the Golden Lion in 2019. He's also received an honorary doctoral degrees from Harvard University in 2009 and from University of Oxford in 2016.
Answer: 1982 - Labyrinth of Passion
1988 - Women on the Verge of a Nervous Breakdown
2004 - Bad Education
2021 - Parallel Mothers
Question: What is the plot of Kuroko's Basketball?
Evidence: The Teiko Middle School basketball team dominated basketball teams within Japan, winning the middle school Nationals for three consecutive years. The star players of the team became known as the "Generation of Miracles". After graduating from middle school, the five star players went to different high schools with top basketball teams. However, there was a rumor that there was another player in the "Generation of Miracles": a phantom sixth man. This mysterious player is now a freshman at Seirin High, a new school with a powerful, if little-known, team. Now, Tetsuya Kuroko – the sixth member of the "Generation of Miracles", and Taiga Kagami – a naturally talented player who spent most of his youth in the US, aim to bring Seirin to the top of Japan by taking on Kuroko's former teammates one by one. The series chronicles Seirin's rise to become Japan's number one high school team. The Generation of Miracles include Ryota Kise, Shintaro Midorima, Daiki Aomine, Atsushi Murasakibara, and Seijuro Akashi.
Answer: Kuroko's Basketball is an anime about basketball. The story starts with Teiko Middle School where 6 talented players are known as the Generation of Miracles and they went undefeated for 3 years. However, all of the players split off for high school. The protagonist, Tetsuya, is the mysterious sixth man who comes to Seirin high school and meets Taiga Kagami, who is a naturally talented American player. The show focuses on this duo beating the rest of the Generation of Miracles to become the top Japanese high school basketball team.
Question: How are character representations from various languages joint?
Evidence: Our formulation of transfer learning builds on work in multi-task learning BIBREF15 , BIBREF9 . We treat each individual language as a task and train a joint model for all the tasks. We first discuss the current state of the art in morphological tagging: a character-level recurrent neural network. After that, we explore three augmentations to the architecture that allow for the transfer learning scenario. All of our proposals force the embedding of the characters for both the source and the target language to share the same vector space, but involve different mechanisms, by which the model may learn language-specific features.
Cross-lingual morphological tagging may be formulated as a multi-task learning problem. We seek to learn a set of shared character embeddings for taggers in both languages together through optimization of a joint loss function that combines the high-resource tagger and the low-resource one. The first loss function we consider is the following:
We treat each individual language as a task and train a joint model for all the tasks.
We seek to learn a set of shared character embeddings for taggers in both languages together through optimization of a joint loss function that combines the high-resource tagger and the low-resource one.
Answer: The answers are shown as follows:
* shared character embeddings for taggers in both languages together through optimization of a joint loss function
Question: If it's called "free" climbing, why do climbers use gear to climb?
Evidence: Free climbing has been called "rock climbing's most commonly mistaken term", with problems including:

Incorrectly assuming that "free climbing" always means solo climbing, i.e. that you must always be alone and without any partner. Free climbing in traditional climbing and sport climbing uses a supporting belayer.
Incorrectly assuming that "free climbing" always means free soloing, i.e. that you must never use any climbing protection equipment. Free climbing in traditional climbing and sport climbing uses climbing protection (but not to aid progression).
Incorrectly assuming that "free climbing" always means onsighting or flashing, i.e. that you must always climb the route first try. Free climbing in traditional climbing and sport climbing also uses the redpoint as a definition of a first free ascent.
Answer: Free climbing refers to a form of rock climbing in which the climber ascends without the use of gear to aid progression. It is a common misunderstanding that free climbing means climbing with no protective gear. Both sport and traditional climbing make use of protective gear to prevent injury and death, and are both considered free climbing. This is in contrast to free solo climbing, another form of free climbing in which the climber uses no protective gear.
Question: What is the largest or biggest land animal?
Answer: The largest or biggest land animal is the African bush elephant. It can reach weights of up to 10000 kgs (or 22000 lbs). However historically there have been dinosaurs that are greater in weight than elephants.
Question: Can you sort the following letters alphabetically: d, h, a, f and y?
Answer: Yes, here is those letters in sorted in alphabetical order : a, d, f, h, y
Question: Why are unsupervised models suited for insight-driven analysis?
Evidence: Topic models (e.g., LDA BIBREF47 ) are usually unsupervised and therefore less biased towards human-defined categories. They are especially suited for insight-driven analysis, because they are constrained in ways that make their output interpretable. Although there is no guarantee that a “topic” will correspond to a recognizable theme or event or discourse, they often do so in ways that other methods do not. Their easy applicability without supervision and ready interpretability make topic models good for exploration. Topic models are less successful for many performance-driven applications. Raw word features are almost always better than topics for search and document classification. LSTMs and other neural network models are better as language models. Continuous word embeddings have more expressive power to represent fine-grained semantic similarities between words.
A topic model provides a different perspective on a collection. It creates a set of probability distributions over the vocabulary of the collection, which, when combined together in different proportions, best match the content of the collection. We can sort the words in each of these distributions in descending order by probability, take some arbitrary number of most-probable words, and get a sense of what (if anything) the topic is “about”. Each of the text segments also has its own distribution over the topics, and we can sort these segments by their probability within a given topic to get a sense of how that topic is used.
One of the most common questions about topic models is how many topics to use, usually with the implicit assumption that there is a “right” number that is inherent in the collection. We prefer to think of this parameter as more like the scale of a map or the magnification of a microscope. The “right” number is determined by the needs of the user, not by the collection. If the analyst is looking for a broad overview, a relatively small number of topics may be best. If the analyst is looking for fine-grained phenomena, a larger number is better.
After fitting the model, it may be necessary to circle back to an earlier phase. Topic models find consistent patterns. When authors repeatedly use a particular theme or discourse, that repetition creates a consistent pattern. But other factors can also create similar patterns, which look as good to the algorithm. We might notice a topic that has highest probability on French stopwords, indicating that we need to do a better job of filtering by language. We might notice a topic of word fragments, such as “ing”, “tion”, “inter”, indicating that we are not handling end-of-line hyphenation correctly. We may need to add to our stoplist or change how we curate multi-word terms.
Topic models (e.g., LDA [Blei et al., 2003]) are usually unsupervised and therefore less biased towards human-defined categories. They are especially suited for insight-driven analysis, because they are constrained in ways that make their output interpretable.
Answer: Because they are constrained in ways that make their output interpretable.
Question: Give me a list of the top five most followed people on Instagram, along with their number of followers.
Answer: 1. Cristiano Ronaldo, 567 millions
2. Lionel Messi, 448 millions
3. Selena Gomez, 407 millions
4. Kylie Jenner, 383 millions
5. Dwayne Johnson, 371 millions
Question: What accuracy does CNN model achieve?
Evidence: FLOAT SELECTED: TABLE IV: Class-wise average IoUs and per-pixel accuracies on the test set. Refer to Table I for full names of abbreviated region types listed at top of the table.
FLOAT SELECTED: TABLE I: Counts for various annotated region types in INDISCAPES dataset. The abbreviations used for region types are given below each region type.
FLOAT SELECTED: TABLE IV: Class-wise average IoUs and per-pixel accuracies on the test set. Refer to Table I for full names of abbreviated region types listed at top of the table.
FLOAT SELECTED: TABLE I: Counts for various annotated region types in INDISCAPES dataset. The abbreviations used for region types are given below each region type.
Answer: Combined per-pixel accuracy for character line segments is 74.79
Question: Why do people enjoy baseball?
Answer: Baseball requires skill, practice, hard work, hand eye coordination and grit.  There are one hundred and fifty plus games per year in the major league, and most players will be on the field for 70% of those games.  There are few thrills better than being in the stands watching your home team win a game in the last inning by hitting a game-winning homerun.
Question: Given this reference text about a video game, when was Donkey Kong released?
Evidence: Nintendo was founded in 1889 as Nintendo Karuta by craftsman Fusajiro Yamauchi and originally produced handmade hanafuda playing cards. After venturing into various lines of business during the 1960s and acquiring a legal status as a public company, Nintendo distributed its first console, the Color TV-Game, in 1977. It gained international recognition with the release of Donkey Kong in 1981 and the Nintendo Entertainment System and Super Mario Bros. in 1985.
Answer: 1981
Question: What is the main tax benefit of a Roth IRA and 401K?
Answer: The main tax benefit of a Roth IRA and 401K is that realized gains from selling investments within the accounts are not taxed.
Question: What type of bike is suitable for children to learn: Balance Bike, Foldable bike, Mountain Bike, Road Bike
Answer: The bike suitable for children to start learning bicycle is Balance Bike
Question: Who is the greatest Boston Red Sox player of all time?
Answer: The Boston Red Sox have had many amazing players over their long history, so it is hard to pick the single best player. Some of the most well-known and beloved players include David Ortiz, Carlton Fisk, Carl Yastrzemski, Ted Williams, Jim Rice, and Pedro Martinez.
Question: Based on the information below, when might people have started baking bread?
Evidence: Agriculture encompasses crop and livestock production, aquaculture, fisheries and forestry for food and non-food products. Agriculture was the key development in the rise of sedentary human civilization, whereby farming of domesticated species created food surpluses that enabled people to live in cities. While humans started gathering grains at least 105,000 years ago, nascent farmers only began planting them around 11,500 years ago. Sheep, goats, pigs and cattle were domesticated around 10,000 years ago. Plants were independently cultivated in at least 11 regions of the world. In the twentieth century, industrial agriculture based on large-scale monocultures came to dominate agricultural output.
Answer: There is not enough information in the passage to determine exactly when this would have happened, but because bread requires grain, it could not have been made prior to 105,000 years ago when humans first started gathering grain.
Question: If there are only two genera remaining, what happened to the other 24?
Evidence: According to the World Register of Marine Species, there are only two genera in this family. Previously there were about 26, but most of these have been reallocated as sub-genera of the remaining two genera, Mycale and Phlyctaenopora:
Answer: Most of the other 24 were reallocated as sub-genera of the remaining two genera.
Question: How are resources adapted to properties of Chinese text?
Evidence: In this paper, we describe our scheme and process in annotating shallow discourse relations using PDTB-style. In view of the differences between English and Chinese, we made adaptations for the PDTB-3 scheme such as removing AltLexC and adding Progression into our sense hierarchy. To ensure the annotation quality, we formulated detailed annotation criteria and quality assurance strategies. After serious training, we annotated 3212 discourse relations, and we achieved a satisfactory consistency of labelling with a Kappa value of greater than 0.85 for most of the indicators. Finally, we display our annotation results in which the distribution of discourse relations and senses differ from that in other corpora which annotate news report or newspaper texts. Our corpus contains more Contingency, Temporal and Comparison relations instead of being governed by Expansion.
In view of the differences between English and Chinese, we made adaptations for the PDTB-3 scheme such as removing AltLexC and adding Progression into our sense hierarchy.
Answer: The answers are shown as follows:
* removing AltLexC and adding Progression into our sense hierarchy