DataHammer/scimrc huggingface dataset:
Question: What methods were used for unsupervised CLWE?
Evidence: Taking the idea of reducing cross-lingual supervision to the extreme, the latest CLWE developments almost exclusively focus on fully unsupervised approaches BIBREF23 , BIBREF24 , BIBREF25 , BIBREF26 , BIBREF27 , BIBREF28 , BIBREF29 , BIBREF30 : they fully abandon any source of (even weak) supervision and extract the initial seed dictionary by exploiting topological similarities between pre-trained monolingual embedding spaces. Their modus operandi can roughly be described by three main components: C1) unsupervised extraction of a seed dictionary; C2) a self-learning procedure that iteratively refines the dictionary to learn projections of increasingly higher quality; and C3) a set of preprocessing and postprocessing steps (e.g., unit length normalization, mean centering, (de)whitening) BIBREF31 that make the entire learning process more robust.
FLOAT SELECTED: Table 1: Configurations obtained by varying components C1, C2, and C3 used in our empirical comparison in §4.
FLOAT SELECTED: Figure 1: General unsupervised CLWE approach.
Model Configurations. Note that C2 and C3 can be equally used on top of any (provided) seed lexicon (i.e., $D^{(1)}$ := $D_0$ ) to enable weakly supervised learning, as we propose here. In fact, the variations of the three key components, C1) seed lexicon, C2) self-learning, and C3) preprocessing and postprocessing, construct various model configurations which can be analyzed to probe the importance of each component in the CLWE induction process. A selection of representative configurations evaluated later in § "Results and Discussion" is summarized in Table 1 .
 three main components: C1) unsupervised extraction of a seed dictionary; C2) a self-learning procedure that iteratively refines the dictionary to learn projections of increasingly higher quality; and C3) a set of preprocessing and postprocessing steps (e.g., unit length normalization, mean centering, (de)whitening)
FLOAT SELECTED: Table 1: Configurations obtained by varying components C1, C2, and C3 used in our empirical comparison in §4.
FLOAT SELECTED: Figure 1: General unsupervised CLWE approach.
representative configurations evaluated later in § "Results and Discussion" is summarized in Table 1 .
Answer: The answers are shown as follows:
* Unsupervised CLWEs. These methods first induce a seed dictionary $D^{(1)}$ leveraging only two unaligned monolingual spaces (C1). While the algorithms for unsupervised seed dictionary induction differ, they all strongly rely on the assumption of similar topological structure between the two pretrained monolingual spaces. Once the seed dictionary is obtained, the two-step iterative self-learning procedure (C2) takes place: 1) a dictionary $D^{(k)}$ is first used to learn the joint space $\mathbf {Y}^{(k)} = \mathbf {X{W}}^{(k)}_x \cup \mathbf {Z{W}}^{(k)}_z$ ; 2) the nearest neighbours in $\mathbf {Y}^{(k)}$ then form the new dictionary $D^{(k+1)}$ . We illustrate the general structure in Figure 1 .
Question: Who is the prime minister of Japan?
Answer: The current prime minister of Japan is Fumio Kishida, who assumed office on the 29th of September 2021. He is also the president of the Liberal Democratic Party (LDP) of Japan. He was born on the 29th of July 1957.
Question: Why was there a lockout during the 1998-1999 NBA season?
Evidence: The 1998–99 NBA season was the Hawks' 50th season in the National Basketball Association, and 31st season in Atlanta. On March 23, 1998, the owners of all 29 NBA teams voted 27–2 to reopen the league's collective bargaining agreement, seeking changes to the league's salary cap system, and a ceiling on individual player salaries. The National Basketball Players Association (NBPA) opposed to the owners' plan, and wanted raises for players who earned the league's minimum salary. After both sides failed to reach an agreement, the owners called for a lockout, which began on July 1, 1998, putting a hold on all team trades, free agent signings and training camp workouts, and cancelling many NBA regular season and preseason games. Due to the lockout, the NBA All-Star Game, which was scheduled to be played in Philadelphia on February 14, 1999, was also cancelled. However, on January 6, 1999, NBA commissioner David Stern, and NBPA director Billy Hunter finally reached an agreement to end the lockout. The deal was approved by both the players and owners, and was signed on January 20, ending the lockout after 204 days. The regular season began on February 5, and was cut short to just 50 games instead of the regular 82-game schedule
Answer: The players and owners failed to reach an agreement on salaries.
Question: Why do people like to travel?
Answer: There are many reasons that people like to travel and the motivation to travel is always unique to each person. The most common reasons are to explore globally famous landmarks, new cultures, different authentic food and to meet new people, which will expand the perspective of different cultures and their value systems.

Also, to unwind and relax from their day to busy schedules. Apart from that with the wide use of social media platforms people have more information and knowledge to get influence. People also travel for research and educational purposes to places such as museums, and historical landmarks.

Overall, traveling can be an enriching, relaxing, and fulfilling experience that will gather beautiful lifelong memories, experiences, and lessons.
Question: Is the idea of learning a linear transformation matrix to map or project word embeddings from the semantic space of one language to that of another first proposed by the authors?
Evidence: Clustering multi-lingual documents has received much attention in natural language processing. Among approaches not using some form of machine translation, one can mention BIBREF1 , who essentially employ a bilingual dictionary to bring some words in the documents to a language-independent form and then to perform clustering. In the section "Experiment Design and Evaluation" we show that our approach based on neural embeddings significantly outperforms their reported results.
 BIBREF2 proposed training joint multi-lingual neural embedding models. Theoretically, this can be used to achieve our aim of language-independent semantic representations for documents. Unfortunately, it demands a large word-aligned parallel corpus. This is not the case with the more recent Trans-gram approach introduced in BIBREF3 , also able to learn multi-lingual models. However, it still needs sentence-aligned corpora to train on (in the size of millions of paired sentences). Large parallel corpora (whether word- or sentence-aligned) are often a scarce resource, especially in the case of under-represented languages.
The approach described in this paper takes as an input only comparable monolingual corpora and bilingual dictionaries in the size of several thousand word pairs. Such resources are much easier to find and evaluate. We employ the idea of learning a linear transformation matrix to map or project word embeddings from the semantic space of one language to that of another. This idea was first proposed in BIBREF4 , who applied it to lexical translation between English, Spanish, Czech and Vietnamese. We extend it from continuous representations of single words or collocations to `semantic fingerprints' of documents as a whole.
We employ the idea of learning a linear transformation matrix to map or project word embeddings from the semantic space of one language to that of another.  This idea was first proposed in (Mikolov et al., 2013a), who applied it to lexical transla tion between English, Spanish, Czech and Vietnamese.
Answer: No.
Question: List five titles by Margaret Atwood.
Answer: The Handmaid's Tale, The Testaments, The Edible Woman, Oryx and Crake, The Year of the Flood
Question: Is wolf a domestic or a wild animal?
Answer: Generally speaking, wolves are regarded as wild animals. While there are cases where wolves have been domesticated, they're not the same as dogs as pets.
Question: What are two useful migration models for using NMT?
Evidence: koehn-knowles:2017:NMT showed that NMT is unable to handle low-resource language pairs as opposed to PBSMT. Transfer learning approaches BIBREF5 , BIBREF6 , BIBREF7 work well when a large helping parallel corpus is available. This restricts one of the source or the target languages to be English which, in our case, is not possible. Approaches involving bi-directional NMT modeling is shown to drastically improve low-resource translation BIBREF11 . However, like most other, this work focuses on translation from and into English.
Remaining options include (a) unsupervised MT BIBREF12 , BIBREF13 , BIBREF14 , (b) parallel sentence mining from non-parallel or comparable corpora BIBREF15 , BIBREF16 , (c) generating pseudo-parallel data BIBREF17 , and (d) MT based on pivot languages BIBREF10 . The linguistic distance between Japanese and Russian makes it extremely difficult to learn bilingual knowledge, such as bilingual lexicons and bilingual word embeddings. Unsupervised MT is thus not promising yet, due to its heavy reliance on accurate bilingual word embeddings. Neither does parallel sentence mining, due to the difficulty of obtaining accurate bilingual lexicons. Pseudo-parallel data can be used to augment existing parallel corpora for training, and previous work has reported that such data generated by so-called back-translation can substantially improve the quality of NMT. However, this approach requires base MT systems that can generate somewhat accurate translations. It is thus infeasible in our scenario, because we can obtain only a weak system which is the consequence of an extremely low-resource situation. MT based on pivot languages requires large in-domain parallel corpora involving the pivot languages. This technique is thus infeasible, because the in-domain parallel corpora for Ja INLINEFORM0 En and Ru INLINEFORM1 En pairs are also extremely limited, whereas there are large parallel corpora in other domains. Section SECREF4 empirically confirms the limit of these existing approaches.
Fortunately, there are two useful transfer learning solutions using NMT: (e) multilingual modeling to incorporate multiple language pairs into a single model BIBREF8 and (f) domain adaptation to incorporate out-of-domain data BIBREF9 . In this paper, we explore a novel method involving step-wise fine-tuning to combine these two methods. By improving the translation quality in this way, we can also increase the likelihood of pseudo-parallel data being useful to further improve translation quality.
Fortunately, there are two useful transfer learning solutions using NMT: (e) multilingual modeling to incorporate multiple language pairs into a single model (Johnson et al., 2017) and (f) domain adaptation to incorporate out-of-domain data (Chu et al., 2017).
Answer: (e) multilingual modeling to incorporate multiple language pairs into a single model and (f) domain adaptation to incorporate out-of-domain data.
Question: Classify each of the following as characters who appear in books by Kevin Kwan or Veronica Roth: Astrid Leong-Teo, Kitty Pong, Colin Khoo, Peik Lin Goh, Charlie Wu, Caleb Prior, Beatrice Prior, Tori, Jeanine Matthews, Tobias Eaton
Answer: Kevin Kwan characters: Astrid Leong-Teo, Kitty Pong, Colin Khoo, Peik Lin Goh, Charlie Wu
Veronica Roth characters: Caleb Prior, Beatrice Prior, Tori, Jeanine Matthews, Tobias Eaton
Question: What were the origins of the American Civil War?
Evidence: Historians who address the origins of the American Civil War today agree that the preservation of slavery in the United States was the principal aim of the 11 Southern states (seven states before the onset of the war and four states after the onset) that declared their secession from the United States (the Union) and united to form the Confederate States of America (known as the "Confederacy"). However, while historians in the 21st century agree on the centrality of the conflict over slavery—it was not just "a cause" of the war but "the cause"—they disagree sharply on which aspects of this conflict (ideological, economic, political, or social) were most important, and on the North’s reasons for refusing to allow the Southern states to secede. Proponents of the pseudo-historical Lost Cause ideology have denied that slavery was the principal cause of the secession, a view that has been disproven by the overwhelming historical evidence against it, notably the seceding states' own secession documents.
Answer: Many historians agree that the issue of slavery was the main cause of the American Civil War.  A total of eleven southern states wanted to preserve slavery and as a result voted to secede from the United States.  These states subsequently declared themselves the Confederate States of America, also known as the Confederacy.  Also most historians agree that slavery was the cause of the war, they have differing views regarding which aspects (idealogical, economic, political, or social) were most important.  Their opinions also differ regarding the Northern States reasons for not allowing the Southern states to succeed from the Union.  Followers of an ideology known as the Lost Cause Idealogy have denied that slavery was the root cause of the war however this view has been disproven by overwhelming evidence, including the Southern states own secession documents.
Question: If 2 carpenters can build 4 chairs in 3 hours, then how many chairs can 6 carpenters build in 6 hours?
Answer: If 2 carpenters can build 4 chairs in 3 hours, then a carpenter can build 1 chair in 1.5 hours. 1 carpenter can build 4 chairs in 6 hours, and 6 carpenters can build 24 chairs in 6 hours.
Question: Identify which instrument is string or percussion: Yuka, Molo
Answer: Molo is string, Yuka is percussion.
Question: What are some good body weight exercises for core and abs?
Answer: Good body weight exercises that strengthen the core and abs are crunches, bicycle crunches, side v-ups, sit ups, planks, dead bugs, and wheel pose.
Question: What is the PGA Championship?
Evidence: The PGA Championship (often referred to as the US PGA Championship or USPGA outside the United States) is an annual golf tournament conducted by the Professional Golfers' Association of America. It is one of the four men's major championships in professional golf.
Answer: The PGA Championship (often referred to as the US PGA Championship or USPGA outside the United States) is an annual golf tournament conducted by the Professional Golfers' Association of America. It is one of the four men's major championships in professional golf.

It was formerly played in mid-August on the third weekend before Labor Day weekend, serving as the fourth and final men's major of the golf season. Beginning in 2019, the tournament is played in May on the weekend before Memorial Day, as the season's second major following the Masters Tournament in April. It is an official money event on the PGA Tour, European Tour, and Japan Golf Tour, with a purse of $11 million for the 100th edition in 2018.

In line with the other majors, winning the PGA gains privileges that improve career security. PGA champions are automatically invited to play in the other three majors (Masters Tournament, U.S. Open, and The Open Championship) and The Players Championship for the next five years, and are eligible for the PGA Championship for life. They receive membership on the PGA Tour for the following five seasons and on the European Tour for the following seven seasons. The PGA Championship is the only one of the four majors that is exclusively for professional players.

The PGA Championship has been held at various venues. Some of the early sites are now quite obscure, but in recent years, the event has generally been played at a small group of celebrated courses.
Question: What does the acronym MEDDPICC stand for?
Answer: MEDDPICC is a sales acronym that stands for Metric, Economic Buyer, Decision Criteria, Decision Process, Paper Process, Identified Pain, Champion and Competition. MEDDPICC is leveraged as a methodology and can be applied to any complex sales process. Sales Managers will use MEDDPICC to inspect deals to determine if the deal is committable for a particular quarter.
Question: What makes the world go around?
Answer: Some say money makes the world go around, others say it is love. It has even been suggested that music is the fuel that makes the world go around. These explanations are however based on human spirituality and needs. As far as other living creatures are concerned, the drive to survive is what makes the world go around. In reality the world physically started going around itself, rotating around its axis, because of the way it was formed.
Question: Extract the names of the Formula One teams Vettel was a part of from the text. Separate them with a comma.
Evidence: Vettel started his Formula One career as a test driver for BMW Sauber in 2006, making a one-off racing appearance in 2007. As part of the Red Bull Junior Team, Vettel appeared for Toro Rosso later that year and was kept as a full-time driver for 2008, where he scored a victory in the Italian Grand Prix to become the then-youngest race winner. Vettel was promoted to Red Bull in 2009. With Red Bull, Vettel won four consecutive titles from 2010 to 2013, the first of which made him the sport's youngest World Champion. In 2013, he set the record for the most consecutive race wins with nine. Vettel signed for Ferrari for 2015 replacing Fernando Alonso and became Mercedes' and Lewis Hamilton's closest challenger in two title fights in 2017 and 2018, although he finished both years as runner-up. He parted ways with Ferrari at the end of the 2020 season to race with Aston Martin for the 2021 and 2022 seasons, before retiring from Formula One at the end of the 2022 season.
Answer: BMW Sauber, Toro Rosso, Red Bull, Ferrari, Aston Martin
Question: Are electric vehicles better for the environment than cars powered by fossil fuels?
Answer: The rise of electric vehicles (or EVs) has been fueled by many factors -- including innovation, acceleration, design and tax breaks -- but the underlying assumption that electric vehicles are less harmful to the environment and may even mitigate global warming has been a primary motivator for hundreds of thousands of buyers.

Despite the virtuous aura of owning an electric vehicle, the jury is still out on whether EVs have a net positive impact on the environment or will do anything to curtail climate change.  That's because, while the experience of driving an EV may feel like a zero-compromise embrace of green energy, the vast industrial network needed to build and power EVs diminishes the halo effect. On the other hand, the fossil fuels that power traditional vehicles are definitely contributing to global warming and leave the world vulnerable to oil shocks and pressure from oil-producing countries. 

Whether EVs are better or worse for the environment is still to be determined. But a more insidious trend is the growing size and power of electric vehicles. Smaller vehicles, traveling fewer miles, represents a proven formula for reducing emissions and reversing climate change. But already, we're seeing the advent of electric trucks and SUVs, which are heavier, loaded with bells and whistles so they require more and more power to move people around. Coupled with the problem of drivers feeling like their EV gives them the right to drive as much as they want and you can see a reality emerging where the problem of Americans driving giant gas guzzlers is being replaced with American driving giant, power-sucking EVs. And that's leading us even faster down the road to environmental disaster.
Question: Why do teenagers disappoint their parents?
Answer: Teenagers by definition are going through a process of maturation and individuation. They are finding their true self, distinct from their parents who have been their role model since infancy. Part of this process requires pushing boundaries set by parents. Parents often interpret this as disobedience and are disappointed. In fact teenagers who seem to be disappointing their parents are merely going through the healthy process of self identification.
Question: How do you play basketball
Answer: Basketball is a game played on a court with five players on each team. There are two baskets that are 10 feet tall on each end of the court and the goal of the game is to get the ball into the basket at the opposing end of the court. Each basket is worth two points, unless the ball is shot from outside of an arc that is painted on the floor. If the shot it made outside of the arc, then it's worth three points. The games are 48 minutes long with 4 even quarters at 12 minutes each. The clock also stops every time a basket is made, the ball goes out of bounds, or a foul is committed. When running with the ball, a player must continuously bounce it off the ground or else it's considered traveling which is a not allowed. Additionally, aggressive contact is also considered a foul. Basketball is more about finesse than it is about physicality. Whichever team scores the most points by the end of the game wins
Question: Which Twitter customer service industries are investigated?
Evidence: We first expand upon previous work and generic dialogue act taxonomies, developing a fine-grained set of dialogue acts for customer service, and conducting a systematic user study to identify these acts in a dataset of 800 conversations from four Twitter customer service accounts (i.e. four different companies in the telecommunication, electronics, and insurance industries). We then aim to understand the conversation flow between customers and agents using our taxonomy, so we develop a real-time sequential SVM-HMM model to predict our fine-grained dialogue acts while a conversation is in progress, using a novel multi-label scheme to classify each turn. Finally, using our dialogue act predictions, we classify conversations based on the outcomes of customer satisfaction, frustration, and overall problem resolution, then provide actionable guidelines for the development of automated customer service systems and intelligent agents aimed at desired customer outcomes BIBREF3 , BIBREF4 .
We first expand upon previous work and generic dialogue act taxonomies, developing a fine-grained set of dialogue acts for customer service, and conducting a systematic user study to identify these acts in a dataset of 800 conversations from four Twitter customer service accounts (i.e. four different companies in the telecommunication, electronics, and insurance industries).
Answer: The answers are shown as follows:
*  four different companies in the telecommunication, electronics, and insurance industries
Question: Which is a species of fish? Shaver or Razorfish
Answer: Razorfish
Question: What is the capital of Norway and when was it founded?
Answer: Oslo is the capital of Norway. It was founded as a city at the end of the Viking Age in 1040 and was given the name Ánslo in 1048 by Harald Hardrada. Haakon V of Norway declared Oslo the capital around 1300. The city was destroyed by a fire in 1624 and then rebuilt.
Question: Write a paragraph on the difficulties of seizure detection among epilepsy patients.
Answer: Seizure detection in epilepsy usually faces the problem of subjectivity where one reviewer's response may differ from another. This makes the seizure classification very difficult, wasting a lot of time. The gold standard, video-EEG, is also time-consuming and resource-intensive. An epilepsy patient can also have multiple types of seizures, making the detection even more difficult. This becomes more challenging when seizure types like hyperkinetic seizures have similar traits to non-epilepsy functional seizures.
Question: Identify which instrument is string or percussion: Slenthem, Scheiholt
Answer: Scheiholt is string, Slenthem is percussion.