DataHammer/scimrc huggingface dataset:
Question: What is the performance of the models on the tasks?
Evidence: An LM's overall performance on *X can be measured simply by taking the proportion of correct predictions across the 67,000 minimal pairs from all paradigms. GPT-2 achieves the highest score and the $n$-gram the lowest. Transformer-XL and the LSTM LM perform in the middle, and at roughly the same level as each other. All models perform well below estimated human agreement (as described in Section SECREF11). The $n$-gram model's poor overall performance confirms *X is not solvable from co-occurrence information alone. Rather, success at *X is driven by the more abstract features learned by neural networks. There are no categories in which the $n$-gram approaches human performance.
We report the 12-category accuracy results for all models and human evaluation in Table TABREF14.
GPT-2 achieves the highest score and the $n$-gram the lowest. Transformer-XL and the LSTM LM perform in the middle, and at roughly the same level as each other.
We report the 12-category accuracy results for all models and human evaluation in Table TABREF14.
Answer: Overall accuracy per model is: 5-gram (60.5), LSTM (68.9), TXL (68.7), GPT-2 (80.1)
Question: Why was the 2023 Women's NCAA basketball championship controversial?
Answer: LSU beat Iowa to win the NCAA women's basketball championship in slightly controversial game. Many fans and pundits observed overly tight officiating resulting in many of the key stars on both teams with quick fouls and spending time on the bench altering the flow of the game requiring more bench players to play than expected. Particularly impactful was a questionable technical foul on Iowa player Caitlin Clark in the second half. Additionally, near the end of the game Angel Reece the LSU star mocked Iowa start Clark as her team won mimicking her soon to be placed championship ring on her hand. The 'trash talk' drove discussion on sportsmanship online among fans and journalists
Question: What are some of the most common social norms in the United States?
Answer: While social norms can vary between regions, some of the most common social norms to most regions in the United States include:
- Greeting people when meeting
- Saying please and thank you
- Holding the door open for someone
- Speaking quietly in a library or other quiet space
- Tipping servers at restaurants and bars
Question: Give me a list of the greatest chess players of all time
Answer: The greatest chess players of all time include Garry Kasparov, Magnus Carlsen, and Bobby Fischer.
Question: Given a reference text bout the Tampa Convention Center, when did it open and how big is it?
Evidence: The Tampa Convention Center is a mid-sized convention center located in downtown Tampa, Florida at the mouth of the Hillsborough River. It has both waterfront views of Tampa Bay and views of the city's skyline. Harbour Island is across the eponymous bridge on the other side of the Garrison Channel. The center is connected to the neighboring Channelside District and Ybor City via the TECO Line Streetcar, which has a station across the street. The center opened in 1990 and encompasses 600,000 square feet (56,000 m2) in total. It has a 200,000 square feet (19,000 m2) exhibit hall, a ballroom capable of accommodating over 2,000 guests, and 36 meeting rooms that can be adjusted to various sizes. The facility hosts over 300 events per year.
Answer: The Tampa Convention Center opened in 1990 and is about 600,000 square feet.
Question: What religion is the oldest in the world?
Answer: The oldest religion in the world is Hinduism. Also known as Sanatana Dharma, Hinduism is one of the major religions in the modern world with over a billion followers. Hinduism contains scriptures dating back 3,000 years ago, and roots and customs dating back over 4,000 years ago. As the world's third largest religion, Hinduism is referred to as a natural religion because of its universal applicability and ability to be understood through study, reason, and experience.
Question: Are results reported only on English datasets?
Evidence: Stanford - Twitter Sentiment Corpus (STS Corpus): STS Corpus contains 1,600K training tweets collected by a crawler from BIBREF0 . BIBREF0 constructed a test set manually with 177 negative and 182 positive tweets. The Stanford test set is small. However, it has been widely used in different evaluation tasks BIBREF0 BIBREF5 BIBREF13 .
Sanders - Twitter Sentiment Corpus: This dataset consists of hand-classified tweets collected by using search terms: INLINEFORM0 , #google, #microsoft and #twitter. We construct the dataset as BIBREF14 for binary classification.
Health Care Reform (HCR): This dataset was constructed by crawling tweets containing the hashtag #hcr BIBREF15 . Task is to predict positive/negative tweets BIBREF14 .
Table IV shows the result of our model for sentiment classification against other models. We compare our model performance with the approaches of BIBREF0 BIBREF5 on STS Corpus. BIBREF0 reported the results of Maximum Entropy (MaxEnt), NB, SVM on STS Corpus having good performance in previous time. The model of BIBREF5 is a state-of-the-art so far by using a CharSCNN. As can be seen, 86.63 is the best prediction accuracy of our model so far for the STS Corpus.
For Sanders and HCR datasets, we compare results with the model of BIBREF14 that used a ensemble of multiple base classifiers (ENS) such as NB, Random Forest (RF), SVM and Logistic Regression (LR). The ENS model is combined with bag-of-words (BoW), feature hashing (FH) and lexicons. The model of BIBREF14 is a state-of-the-art on Sanders and HCR datasets. Our models outperform the model of BIBREF14 for the Sanders dataset and HCR dataset.
Stanford - Twitter Sentiment Corpus (STS Corpus): STS Corpus contains 1,600K training tweets collected by a crawler from BIBREF0 . BIBREF0 constructed a test set manually with 177 negative and 182 positive tweets. The Stanford test set is small. However, it has been widely used in different evaluation tasks BIBREF0 BIBREF5 BIBREF13 .

Sanders - Twitter Sentiment Corpus: This dataset consists of hand-classified tweets collected by using search terms: INLINEFORM0 , #google, #microsoft and #twitter. We construct the dataset as BIBREF14 for binary classification.

Health Care Reform (HCR): This dataset was constructed by crawling tweets containing the hashtag #hcr BIBREF15 . Task is to predict positive/negative tweets BIBREF14 .
Table IV shows the result of our model for sentiment classification against other models. We compare our model performance with the approaches of BIBREF0 BIBREF5 on STS Corpus. 
For Sanders and HCR datasets, we compare results with the model of BIBREF14 that used a ensemble of multiple base classifiers (ENS) such as NB, Random Forest (RF), SVM and Logistic Regression (LR). 
Answer: Yes.
Question: Is new evaluation metric extension of ROGUE?
Evidence: CIC is a suitable complementary metric to ROUGE because it accounts for the most important information within each dialog domain. CIC can be applied to any summarization task with predefined essential entities. For example, in news summarization the proper nouns are the critical information to retain.
CIC is a suitable complementary metric to ROUGE because it accounts for the most important information within each dialog domain. CIC can be applied to any summarization task with predefined essential entities.
Answer: No.
Question: Which of the following are women scientists: Marie Curie, Elizabeth Blackwell, Jane Goodall, Rosalind Franklin, Ada Lovelace, Maria Mitchell, Archimedes, Albert Einstein, Ernest Rutherford, Alfred Nobel, Alexander Fleming, Michael Faraday, Niels Bohr, Stephen Hawking, Alan Turing.
Answer: Marie Curie, Elizabeth Blackwell, Jane Goodall, Rosalind Franklin, Ada Lovelace, Maria Mitchell are women scientists.
Question: What are the words of House Tully?
Answer: "Family, Duty, Honor."
Question: Was the new deal successful or a failure to solve the problems of the Great Depression?
Answer: The new deal was a success to solve the problems caused by the Great Depression because he took action quickly, he passed many acts, and he kept the moral up for the people.  Franklin Roosevelt writes "This is no usolvable prroblem if we face it wisely and courageously.  It can be accomplished in part by direct recruiting by the Government itself, treating the task as we would treat the emergency of a war."  Roosevelt is saying that unlike Hoover, he was going to take action on what was happening.  Anything he will do will be treated as if it was war because it was affecting them as much as war would.  The New Deal Legislation shows that Franklin Roosevelt had a god relationship with Congress.  11 new acts were passed in 6 years while Rosevelt was in office.  This helps people get jobs, lower prices, and help people get money they deserve.  Roosevelt says "This great Nation will endure as it has endured, will revive and will prosper.  This shows that Rosevelt knows how to lead people even in the hard time.  He knew while it was bad, everyone will look to him, so he can't seem scared and he can't kill the moral of the people.  With all of this, Roosevelt was able to lead the country away from the Great Depression and started to get them out of it.
Question: What is the The Science Laureates of the United States Act of 2013
Answer: The Science Laureates of the United States Act of 2013 (H.R. 1891) is a bill that would create the position of Science Laureate of the United States, meant to be similar to the United States Poet Laureate. The Science Laureate would spend their term traveling around the country promoting science and research to students and the general public. The bill was introduced into the United States House of Representatives during the 113th United States Congress.
Question: What is the difference between speaker-open and speaker-closed setting?
Evidence: In the speaker-closed condition, two episodes were set aside from each speaker as development and test sets. Thereafter, the total sizes of the development and test sets turns out to be 1585 IPUs spanning 2 hours 23 minutes and 1841 IPUs spanning 2 hours and 48 minutes respectively. The ASR model is trained with the rest data. In the speaker-open condition, all the data except for the test speaker's were used for training As it would be difficult to train the model if all of the data of speaker KM or UT were removed, experiments using their speaker-open conditions were not conducted.
In the speaker-closed condition, two episodes were set aside from each speaker as development and test sets. Thereafter, the total sizes of the development and test sets turns out to be 1585 IPUs spanning 2 hours 23 minutes and 1841 IPUs spanning 2 hours and 48 minutes respectively. The ASR model is trained with the rest data. In the speaker-open condition, all the data except for the test speaker's were used for training As it would be difficult to train the model if all of the data of speaker KM or UT were removed, experiments using their speaker-open conditions were not conducted.
Answer: The answers are shown as follows:
* In the speaker-closed condition, two episodes were set aside from each speaker as development and test sets.
* In the speaker-open condition, all the data except for the test speaker's were used for training
Question: Is their dataset a new dataset?
Evidence: Accuracy in any machine learning tasks can be enhanced either by improving a machine learning model or by using more in-domain training data. Current state of the art models BIBREF6 , BIBREF7 , BIBREF8 , BIBREF11 improve over AS Reader's accuracy on CBT NE and CN datasets by 1-2 percent absolute. This suggests that with current techniques there is only limited room for improvement on the algorithmic side.
The other possibility to improve performance is simply to use more training data. The importance of training data was highlighted by the frequently quoted Mercer's statement that “There is no data like more data.” The observation that having more data is often more important than having better algorithms has been frequently stressed since then BIBREF13 , BIBREF14 .
As a step in the direction of exploiting the potential of more data in the domain of text comprehension, we created a new dataset called BookTest similar to, but much larger than the widely used CBT and CNN/DM datasets.
As a step in the direction of exploiting the potential of more data in the domain of text comprehension, we created a new dataset called BookTest similar to, but much larger than the widely used CBT and CNN/DM datasets.
Answer: Yes, it is similar to CBT and CNN/DM datasets, but much larger.
Question: Did Ghana lose by 100 against India in a soccer game?
Answer: This game actually didn't happen but Ghanaians and the entire nation some believe it did and tell stories about it. Our parents describe the game as very intriguing filled with mythical black magic and powers. It is believe that the soccer ball turned in the course of the game turned into different sorts of objects every time Ghana had possession. This however aided the Indian team to put up 100 goals whereas Ghana only scored 1. Lastly, legend has it that the Ghanaian player that scored the only goal for Ghana died afterwards
Question: Which of these sentences is correct: "If I was you, I would do it" or "If I were you, I would do it"?
Answer: The correct sentence is "If I were you, I would do it"." This is the subjunctive form of English. It should be used when a hypothetical is contrary to fact. In this case, "I" is not "you," so the subjunctive form should be used. In first person, the form of "be" used for the subjunctive mood is "were."
Question: How many Alabama football players have won the Heisman?
Evidence: The Alabama Crimson Tide football program represents the University of Alabama (variously Alabama, UA, or Bama) in the sport of American football. The team competes in the Football Bowl Subdivision (FBS) of the National Collegiate Athletic Association (NCAA) and the Western Division of the Southeastern Conference (SEC). The team's head coach is Nick Saban, who has led the Tide to six national championships over his tenure. The Crimson Tide is among the most storied and decorated football programs in NCAA history. Since beginning play in 1892, the program claims 18 national championships, including 13 wire-service (AP or Coaches') national titles in the poll-era, and five other titles before the poll-era. From 1958 to 1982, the team was led by Hall of Fame coach Paul "Bear" Bryant, who won six national titles with the program. Despite numerous national and conference championships, it was not until 2009 that an Alabama player received a Heisman Trophy, when running back Mark Ingram II became the university's first winner. In 2015, Derrick Henry became the university's second Heisman winner. The Crimson Tide won back to back Heisman trophies in 2020 and 2021, with DeVonta Smith and Bryce Young.
Answer: The Alabama Crimson Tide football program has produced four Heisman trophy winners. The first Crimson Tide player to win the Heisman was running back Mark Ingram II in 2009. Running back Derrick Henry won the Heisman trophy in 2015. Alabama had back-to-back Heisman trophy winners in 2020 and 2021, DeVonta Smith and Bryce Young.
Question: What is a personalized sales email?
Answer: A personalized sales email is an email written to a specific person at a company. This type of email is tailored to a prospective customer in a way that touches upon why you are reaching out to that person and why you are reaching out to that person right now. An initial personalized email aims to spark interest in potential buyers, hoping they agree to discuss the value they might gain by purchasing your offering.
Question: How do you make a Negroni?
Answer: Here is how to make a Negroni cocktail:

Ingredients:
- Gin
- Campari
- Sweet Vermouth
- Orange peel
- Ice for mixing
- Ice for serving; Single large ice "rock" generally preferred

Bar tools needed:
- Mixing glass
- Mixing spoon
- Strainer
- Glass for serving; preferably a cocktail tumbler style glass

Making the cocktail

- Place the ice (or ice rock) in the serving glass
- Pour 1 ounce each of the gin, Campari, and vermouth into the mixing glass
- Add 5-10 ice cubes to the mixing glass
- Using the mixing spoon, stir the ingredients vigorously for 20-30 seconds
- Using the strainer, pour the cocktail into the serving glass
- Twist the orange peel to release oil and aroma; rub orange peel around rim of glass; place orange peel into the cocktail
- Enjoy!

If you enjoy the negroni, you can experiment with the ingredients.  Many enjoy mezcal as a replacement for the gin.  Also, you can swap out Campari for other bitter style aperitifs; St. George's Bruto Americano is a good example of a possible substitute.
Question: What are some highlights of Lionel Messi's career goals?
Evidence: Lionel Messi is an Argentine professional footballer who has represented the Argentina national football team as a forward since his debut in 2005. Since then, Messi has scored 102 goals in 174 international appearances, making him the country's all-time top scorer; he surpassed Gabriel Batistuta's record of 54 goals with a free kick against the United States in the semi-final of the Copa América Centenario on 21 June 2016. He also holds the record for most goals by a South American male, surpassing Pelé‘s 77 goals with a hat-trick against Bolivia in September 2021. Messi made his debut for Argentina in a 2–1 away win over Hungary on 17 August 2005, and scored his first international goal a year later in his sixth appearance, against Croatia.

Messi's goal against Serbia and Montenegro, on 16 June 2006, at the age of 18 years and 357 days, made him the youngest-ever scorer for Argentina at a FIFA World Cup. He has scored nine international hat-tricks, and has netted twice in a match on ten occasions. In a June 2022 friendly against Estonia, Messi scored five goals in a match for Argentina for the first time. Out of all his opponents, Messi has scored the most against Bolivia, netting eight goals in total.
Answer: He is his country's all-time top scorer with 102 goals in 174 international appearances. He also is the South American male with most goals, surpassing Pelé's 77 goals. He also was the youngest-ever scorer for Argentina at a Fifa World Cup. He has scored nine international hat-tricks, and scored five times in a match for Argentina for the first time against Estonia in June 2022.
Question: Identify which instrument is string or percussion: Erxian, Alfaia
Answer: Erxian is string, Alfaia is percussion.
Question: Tell me whether these animals are a canine or a feline: French Bulldog, Siamese Cat, Sharpei
Answer: The french bulldog is a canine, the Siamese Cat is a feline and the Sharpei is a canine.
Question: Why are pulse tools used in product assembly over impact wrenches?
Evidence: Impact wrenches are widely used in many industries, such as automotive repair, heavy equipment maintenance, product assembly, major construction projects, and any other instance where a high torque output is needed. For product assembly, a pulse tool is commonly used, as it features a reactionless tightening while reducing the noise levels the regular impacts suffer from. Pulse tools use oil as a medium to transfer the kinetic energy from the hammer into the anvil. This gives a smoother impulse, a slightly lower torque to weight ratio and a possibility to design a shut off mechanism that shuts the tool down when achieving the correct torque. Pulse tools are not referred to as "impact wrenches" as the performance and technology are not the same.
Answer: Pulse tools are used for product assembly because they have reactionless tightening and are able to reduce noise levels
Question: Is machine learning system underneath similar to image caption ML systems?
Evidence: Our conversational agent uses two architectures to simulate a specialized reminiscence therapist. The block in charge of generating questions is based on the work Show, Attend and Tell BIBREF13. This work generates descriptions from pictures, also known as image captioning. In our case, we focus on generating questions from pictures. Our second architecture is inspired by Neural Conversational Model from BIBREF14 where the author presents an end-to-end approach to generate simple conversations. Building an open-domain conversational agent is a challenging problem. As addressed in BIBREF15 and BIBREF16, the lack of a consistent personality and lack of long-term memory which produces some meaningless responses in these models are still unresolved problems.
Our conversational agent uses two architectures to simulate a specialized reminiscence therapist. The block in charge of generating questions is based on the work Show, Attend and Tell BIBREF13. This work generates descriptions from pictures, also known as image captioning.
Answer: Yes.
Question: What is MRC?
Evidence: Machine reading comprehension (MRC) requires reasoning about both the knowledge involved in a document and knowledge about the world. However, existing datasets are typically dominated by questions that can be well solved by context matching, which fail to test this capability. To encourage the progress on knowledge-based reasoning in MRC, we present knowledge-based MRC in this paper, and build a new dataset consisting of 40,047 question-answer pairs. The annotation of this dataset is designed so that successfully answering the questions requires understanding and the knowledge involved in a document. We implement a framework consisting of both a question answering model and a question generation model, both of which take the knowledge extracted from the document as well as relevant facts from an external knowledge base such as Freebase/ProBase/Reverb/NELL. Results show that incorporating side information from external KB improves the accuracy of the baseline question answer system. We compare it with a standard MRC model BiDAF, and also provide the difficulty of the dataset and lay out remaining challenges.
Machine reading comprehension (MRC) requires reasoning about both the knowledge involved in a document and knowledge about the world.
Answer: It refers to Machine reading comprehension.
Question: What would you do if you had all the resources in the world and nothing to worry about?
Answer: Wow, as dreamy as it sounds, I would love to live that dream. I would like to go by see, living on a cliff in a glass house that shows both the sunrise and sunset. And it is windy with a big garden where my dog can run and play. I really can not imagine the sun bask, knowing that I don't have to go back from this vacation ever that this is my home and I can just do this alone for the rest of my life :)
Question: Why can't I wake up early in the morning?
Answer: It is the problem of your geography. You just have to travel to a place that is a couple of hours behind your current timezone.
Question: From the example given in this paragraph, what is an eigenvector?
Evidence: The Mona Lisa example pictured here provides a simple illustration. Each point on the painting can be represented as a vector pointing from the center of the painting to that point. The linear transformation in this example is called a shear mapping. Points in the top half are moved to the right, and points in the bottom half are moved to the left, proportional to how far they are from the horizontal axis that goes through the middle of the painting. The vectors pointing to each point in the original image are therefore tilted right or left, and made longer or shorter by the transformation. Points along the horizontal axis do not move at all when this transformation is applied. Therefore, any vector that points directly to the right or left with no vertical component is an eigenvector of this transformation, because the mapping does not change its direction. Moreover, these eigenvectors all have an eigenvalue equal to one, because the mapping does not change their length either.
Answer: An eigenvector of a mapping is any vector that does not change direction when the mapping is applied to it.
Question: What essential tools do I need in my toolbox?
Answer: Hammer, screwdriver, adjustable wrench, pliers, level