DataHammer/scimrc huggingface dataset:
Question: What optimizer does the team introduce in their research?
Evidence: Conventional automatic speech recognition (ASR) systems typically consist of several independently learned components: an acoustic model to predict context-dependent sub-phoneme states (senones) from audio, a graph structure to map senones to phonemes, and a pronunciation model to map phonemes to words. Hybrid systems combine hidden Markov models to model state dependencies with neural networks to predict states BIBREF0 , BIBREF1 , BIBREF2 , BIBREF3 . Newer approaches such as end-to-end (E2E) systems reduce the overall complexity of the final system.
Our research builds on prior work that has explored using time-delay neural networks (TDNN), other forms of convolutional neural networks, and Connectionist Temporal Classification (CTC) loss BIBREF4 , BIBREF5 , BIBREF6 . We took inspiration from wav2letter BIBREF6 , which uses 1D-convolution layers. Liptchinsky et al. BIBREF7 improved wav2letter by increasing the model depth to 19 convolutional layers and adding Gated Linear Units (GLU) BIBREF8 , weight normalization BIBREF9 and dropout.
By building a deeper and larger capacity network, we aim to demonstrate that we can match or outperform non end-to-end models on the LibriSpeech and 2000hr Fisher+Switchboard tasks. Like wav2letter, our architecture, Jasper, uses a stack of 1D-convolution layers, but with ReLU and batch normalization BIBREF10 . We find that ReLU and batch normalization outperform other activation and normalization schemes that we tested for convolutional ASR. As a result, Jasper's architecture contains only 1D convolution, batch normalization, ReLU, and dropout layers – operators highly optimized for training and inference on GPUs.
It is possible to increase the capacity of the Jasper model by stacking these operations. Our largest version uses 54 convolutional layers (333M parameters), while our small model uses 34 (201M parameters). We use residual connections to enable this level of depth. We investigate a number of residual options and propose a new residual connection topology we call Dense Residual (DR).
Integrating our best acoustic model with a Transformer-XL BIBREF11 language model allows us to obtain new state-of-the-art (SOTA) results on LibriSpeech BIBREF12 test-clean of 2.95% WER and SOTA results among end-to-end models on LibriSpeech test-other. We show competitive results on Wall Street Journal (WSJ), and 2000hr Fisher+Switchboard (F+S). Using only greedy decoding without a language model we achieve 3.86% WER on LibriSpeech test-clean.
This paper makes the following contributions:
We introduce NovoGrad, a variant of the Adam optimizer [15] with a smaller memory footprint.
Answer: NovoGrad.
Question: Classify the below Noble prize winners based on the country they are from.
Rabindranath Tagore, Chandrasekhara Venkata Raman, Amartya Kumar Sen, Joseph John Thomson, Ernest Rutherford, Niels Bohr
Answer: India- Rabindranath Tagore, Chandrasekhara Venkata Raman, Amartya Kumar Sen, Joseph John Thomson, Ernest Rutherford, Niels Bohr
UK- Joseph John Thomson
New Zealand - Ernest Rutherford
Denmark - Niels Bohr
Question: Where did Allen Eager grow up?
Evidence: Allen Eager was born in New York City on January 10, 1927. He grew up in the Bronx. According to Denise McCluggage, Eager could read aged 3, and learned to drive at the age of 9 with the help of his mother, after she caught him driving a garbage truck near the hotels that his parents owned in the Catskill Mountains. He took clarinet lessons with David Weber of the New York Philharmonic at the age of 13.
Answer: Allen Eager grew up in the Bronx.
Question: Why is the glass ceiling better for minority women?
Evidence: A glass ceiling is a metaphor usually applied to women, used to represent an invisible barrier that prevents a given demographic from rising beyond a certain level in a hierarchy. No matter how invisible the glass ceiling is expressed, it is actually a difficult obstacle to overcome. The metaphor was first used by feminists in reference to barriers in the careers of high-achieving women. It was coined by Marilyn Loden during a speech in 1978. In the United States, the concept is sometimes extended to refer to racial inequality in the United States. Minority women in white-majority countries often find the most difficulty in "breaking the glass ceiling" because they lie at the intersection of two historically marginalized groups: women and people of color. East Asian and East Asian American news outlets have coined the term "bamboo ceiling" to refer to the obstacles that all East Asian Americans face in advancing their careers. Similarly, a multitude of barriers that refugees and asylum seekers face in their search for meaningful employment is referred to as canvas ceiling.
Answer: Actually, the glass ceiling is considered worse for minority women, not better. This is because they have to face both racial and gender inequalities.
Question: What is the mascot of Cornell University?
Answer: Cornell's mascot is "Big Red" or "Touchdown the Bear." It's common to hear Cornellian's chant "Go Big Red" at sporting events.
Question: Which state's capital is inaccessible by road?
Answer: Juneau, Alaska is inaccessible by road, but cars can get to the city via ferry.
Question: How are the models evaluated?
Evidence: We consider the following metrics for automatic evaluation of different submissions. Joint goal accuracy has been used as the primary metric to rank the submissions.
Active Intent Accuracy: The fraction of user turns for which the active intent has been correctly predicted.
Requested Slot F1: The macro-averaged F1 score for requested slots over all eligible turns. Turns with no requested slots in ground truth and predictions are skipped.
Average Goal Accuracy: For each turn, we predict a single value for each slot present in the dialogue state. This is the average accuracy of predicting the value of a slot correctly.
Joint Goal Accuracy: This is the average accuracy of predicting all slot assignments for a given service in a turn correctly.
We consider the following metrics for automatic evaluation of different submissions. Joint goal accuracy has been used as the primary metric to rank the submissions.

Active Intent Accuracy: The fraction of user turns for which the active intent has been correctly predicted.

Requested Slot F1: The macro-averaged F1 score for requested slots over all eligible turns. Turns with no requested slots in ground truth and predictions are skipped.

Average Goal Accuracy: For each turn, we predict a single value for each slot present in the dialogue state. This is the average accuracy of predicting the value of a slot correctly.

Joint Goal Accuracy: This is the average accuracy of predicting all slot assignments for a given service in a turn correctly.
Answer: The answers are shown as follows:
* Active Intent Accuracy
* Requested Slot F1
* Average Goal Accuracy
* Joint Goal Accuracy
Question: Can AI take my job
Answer: While it is possible for AI to do a piece of work that is done by a human, it is unlikely that AI will make humans redundant in the workplace.  What is more plausible is that AI will change the nature of how humans work, enabling greater productivity or becoming a validation/verification process.

A good example of this is GPS.  For years, taxi drivers used their knowledge of an area to take people from one place to another, but with the invention of GPS, this local knw;edge became less valuable (but not redundant).  There was not a reduction in Taxi drives, if anything, there were more Taxis available to the general public.

The spell checker has been in software for decades, but it is still down to the individual to clarify their specific meaning and validate the final output, rather than relying purely on what a computer generates.
Question: What are the three major Abrahamic religions?
Answer: Judaism, Christianity and Islam are the three largest Abrahamic religions
Question: List 10 best switch games of all time.
Answer: According to the metacritic website, the top 10 switch games of all time are:

1. The Legend of Zelda: Breath of the Wild
2. Super Mario Odyssey
3. Portal Companion Collection
4. The House in Fata Morgana - Dreams of the Revenants Edition
5. Tetris Effect: Connected
6. Metroid Prime Remastered
7. Persona 5 Royal
8. Hades
9. Divinity: Original Sin II - Definitive Edition
10. Ori and the Will of the Wisps

The top 10 lists from other websites may vary.
Question: Best places to visit in India During Winter to experience Snowfall
Answer: Kashmir, Manali, Shimla, Sikkim, Tawang
Question: Extract all the locations in the text
Evidence: Todd, third son of Ira and Sally (Hmman) Todd, was born in Hartwick, New York., March 4, 1813. He had spent one year at Amherst College, before entering as Sophomore at Yale College, where he graduated in 1836. He taught a high school in Canaan, Conn., until the spring of 1837, when he began law studies with Judge Arphaxad Loomis, of Little Falls, New York. Upon his admission to the bar in 1839, he decided to emigrate to the West. He selected St. Louis and arrived there in November, 1839, beginning practice in March, 1840. He gave special attention to questions affecting real property, and achieved distinguished success in litigated cases of this nature. Through apprehensions with regard to his health, he retired in 1860, at a comparatively early age, from active practice, confining himself thereafter to office consultations. He declined all political nominations until 1854, when he was elected to the Missouri House of Representatives. In 1860 he was an unsuccessful candidate for US Congress on the Bell and Everett ticket. In 1875, he was a member of the convention which revised the Constitution of Missouri. He was a director of Washington University, in St. Louis, and served gratuitously for fifteen years in its Law Department as lecturer. Among his students was Lemma Barkaloo, the first female law student in the United States. After a month's illness, he died at his home in St. Louis, of meningitis, April 30, 1885, in his 73rd year.
Answer: Hartwick, New York
Canaan, Connecticut
Little Falls, New York
St Louis
Question: What is it like to live in New Zealand?
Answer: New Zealand is considered a really safe country to live in. Politics are quite liberal with the left and the right political parties not having a lot of difference between them. The climate is very diverse from the top of the North Island to the bottom of the South Island however all seasons are generally pretty mild without many extreme weather events. Housing is a big issue in New Zealand, with house prices being extremely high compared to income earned. The culture is could be described as laid back and easy going.
Question: Which TV show features a team of teenagers that power up with powers given to them by Zordon to save the world from monsters?
Answer: The Mighty Morphin Power Rangers.
Question: What are some of the most popular tourist attractions to visit in Sydney?
Answer: Sydney has many famous landmarks and attractions, with the most famous being the Sydney Harbour Bridge and the Sydney Opera House, situated on the foreshore of Sydney harbour. These two landmarks are the iconic images of Sydney and are often viewed from public ferries, either a ferry taken to visit Manly Beach or to Watsons bay. Visitors to Sydney also often visit the historical Rocks district to see the oldest surviving buildings in the city and learn about the town's early history. The view from the top of the Sydney Tower is also popular, with views out to the Pacific Ocean over the famous Bondi Beach. Also located on Sydney harbour is the Taronga Park Zoo, with animals both domestic and imported and a spectacular view over the harbour. Further out of town it is common to visit the Blue Mountains, with the Three Sisters rock formation at Katoomba being particularly popular.
Question: Describe a scary moment in a storm.
Answer: I live in Oklahoma, so we see our fair share of storms. Storm sirens are so common that I don't take cover every time they go off. Instead, it's normal for me to watch the radar when a storm system is moving through to see where the tornados are and how close they are to me. 

Once, the radar showed a tornado southwest of our house - moving towards us. When it was within a couple miles of us, my wife took the dogs and blankets and went to our safe place - an internal bathroom. I stood back from the windows and watched the tv. From my position, I could see out the back windows which faced west - southwest. The weather showed that the tornado was right on top of us. I watched out the window as a fragment of a four by four, about a foot and a half long, flipped up from the ground and tumbled across the lawn. 

It was that moment that I decided I had watched enough and stepped into the bathroom to join my wife and the dogs. The storm blew over us. The tornado wasn't on the ground as it passed by, but it was definitely and intense several minutes as we waited. 

I have seen my fair share of storms and had a number of close calls with tornados. This definitely falls in one of my top 5.
Question: Write a short passage explaining why someone should become a fan of the Pittsburgh Steelers.
Answer: The Pittsburgh Steelers are one of the great franchises in the National Football League. The Steelers have a rich and storied history, including six Super Bowl victories. The Steelers have been owned by the Rooney family from their inception, and are renowned for their organizational excellence. The Steelers are also known for having a vast global diaspora of fans, all of whom proudly wave and display their "Terrible Towels" to cheer on them on. Additionally, their current roster is filled with exciting young talent, including Kenny Pickett, George Pickens, and Najee Harris. The Steelers are also leaders in propagating diversity within their organization, especially within their leadership. Lastly, Mike Tomlin, the head coach of the Pittsburgh Steelers, is a proven winner, and has never had a losing season while coaching the Steelers. The Steelers are a fun team to watch, a fun team to cheer for, and a team that has great pride in their values on and off the field.
Question: What task is set for testing the model?
Evidence: Quality estimation (QE) refers to the task of measuring the quality of machine translation (MT) system outputs without reference to the gold translations BIBREF0 , BIBREF1 . QE research has grown increasingly popular due to the improved quality of MT systems, and potential for reductions in post-editing time and the corresponding savings in labor costs BIBREF2 , BIBREF3 . QE can be performed on multiple granularities, including at word level, sentence level, or document level. In this paper, we focus on quality estimation at word level, which is framed as the task of performing binary classification of translated tokens, assigning “OK” or “BAD” labels.
Early work on this problem mainly focused on hand-crafted features with simple regression/classification models BIBREF4 , BIBREF5 . Recent papers have demonstrated that utilizing recurrent neural networks (RNN) can result in large gains in QE performance BIBREF6 . However, these approaches encode the context of the target word by merely concatenating its left and right context words, giving them limited ability to control the interaction between the local context and the target word.
In this paper, we propose a neural architecture, Context Encoding Quality Estimation (CEQE), for better encoding of context in word-level QE. Specifically, we leverage the power of both (1) convolution modules that automatically learn local patterns of surrounding words, and (2) hand-crafted features that allow the model to make more robust predictions in the face of a paucity of labeled data. Moreover, we further utilize stacked recurrent neural networks to capture the long-term dependencies and global context information from the whole sentence.
We tested our model on the official benchmark of the WMT18 word-level QE task. On this task, it achieved highly competitive results, with the best performance over other competitors on English-Czech, English-Latvian (NMT) and English-Latvian (SMT) word-level QE task, and ranking second place on English-German (NMT) and German-English word-level QE task.
We tested our model on the official benchmark of the WMT18 word-level QE task.
Answer: The WMT18 word-level QE task.
Question: How many steps does discursive analysis of a document usually include?
Evidence: Rhetorical Structure Theory (RST) BIBREF0 is a technique of Natural Language Processing (NLP), in which a document can be structured hierarchically according to its discourse. The generated hierarchy, a tree, provides information associated with the boundaries of the discourse segments and related to their importance and dependencies. The figure FIGREF1 shows an example of such a rethorical tree. In the rethorical parsing process, the text has been divided into five units. In the figure FIGREF1, the arrow that leaves the unit (2) towards the unit (1) symbolizes that the unit (2) is the satellite of the unit (1), which is the core in a “Concession” relationship. In turn, the units (1) and (2) comprise the nucleus of three “Demonstration” relationships.
The discursive analysis of a document normally includes three consecutive steps: 1) discursive segmentation; 2) detection of the discursive relations; 3) construction of the hierarchical rhetorical tree. Regarding the discursive segmentation, there are segmenters in several languages. However, each piece depends on sofisticated linguistic resources, which complicates the reproduction of the experiments in other languages. Consequently, the development of multilingual systems using discursive analysis are yet to be developed. Diverse applications based on the latest technologies require at least one of the three steps mentioned above BIBREF1, BIBREF2, BIBREF3. In this context, the idea of exploring the architecture of a generic system that is able not only of segmenting a text correctly but also of adapting it to any language, was a great motivation of this research work.
In this article we show the preliminary results of a generic segmenter composed of several systems (different segmentation strategies). In addition, we describe an automatic evaluation protocol of discursive segmentation. The article is composed by the following sections: state of the art (SECREF2), which presents a brief bibliographic review; Description of the Annodis (SECREF3) corpus used in our tests and of the general architecture of the proposed systems (SECREF4); Segmentation strategies (SECREF5), which characterizes the different methods implemented to segment the text; results of our numerical experiments (sec:experiments); and we conclude with our conclusions and perspectives (SECREF7).
In the figure 1, the arrow that leaves the unit (2) towards the unit (1) symbolizes that the unit (2) is the satellite of the unit (1), which is the core in a “Concession” relationship. In turn, the units (1) and (2) comprise the nucleus of three “Demonstration” relationships. The discursive analysis of a document normally includes three consecutive steps: 1) discursive segmentation; 2) detection of the discursive relations; 3) construction of the hierarchical rhetorical tree.
Answer: Three consecutive steps. 1) discursive segmentation; 2) detection of the discursive relations; 3) construction of the hierarchical rhetorical tree.
Question: What are people from Wisconsin also referred to as?
Answer: Some people refer to people from Wisconsin as Cheeseheads because of the amount of dairy that is produced by the state.  It was a derogatory term set in from a local sports rivalry with people from Illinois, however the Cheeseheads from Wisconsin embraced it, and now wear Cheesehead hats to local sporting events.
Question: Are PIEs extracted automatically subjected to human evaluation?
Evidence: For parser-based extraction, systems with and without in-context parsing, ignoring labels, and ignoring directionality are tested. For the three string-based extraction methods, varying numbers of intervening words and case sensitivity are evaluated. Evaluation is done using the development set, consisting of 22 documents and 1112 PIE candidates, and the test set, which consists of 23 documents and 1127 PIE candidates. For each method the best set of parameters and/or options is determined using the development set, after which the best variant by F1-score of each method is evaluated on the test set.
Since these documents in the corpus are exhaustively annotated for PIEs (see Section SECREF40), we can calculate true and false positives, and false negatives, and thus precision, recall and F1-score. The exact spans are ignored, because the spans annotated in the evaluation corpus are not completely reliable. These were automatically generated during candidate extraction, as described in Section SECREF45. Rather, we count an extraction as a true positive if it finds the correct PIE type in the correct sentence.
Evaluation is done using the development set, consisting of 22 documents and 1112 PIE candidates, and the test set, which consists of 23 documents and 1127 PIE candidates. For each method the best set of parameters and/or options is determined using the development set, after which the best variant by F1-score of each method is evaluated on the test set.

Since these documents in the corpus are exhaustively annotated for PIEs (see Section SECREF40), we can calculate true and false positives, and false negatives, and thus precision, recall and F1-score.
Answer: Yes.
Question: Which of the following from this list are types of flowers and which are names of European countries: roses, Norway, tulips, the Netherlands, Sweden, France, Spain, Greece, Italy, and sunflowers.
Answer: The types of flowers from this list are: tulips, roses and sunflowers. The European countries are Norway, the Netherlands, Sweden, France, Spain, Greece, and Italy.
Question: What is the difference between a guitar and a ukulele?
Answer: While a ukulele might be thought of as a small guitar, there are actually numerous differences between the two instruments:
1. A ukulele has 4 strings while a guitar has 6 strings or sometimes 12
2. A ukulele's 4 strings are tuned differently from any consecutive series of a guitar's 4 strings
Question: What are some areas that firefighters can safely stay in while fighting a wildfire?
Evidence: Outcomes from Project Vesta have been integrated into firefighter training in Australia and are beginning to appear in the United States.

Firefighters try to stay out of the dead man zone at all times, working from safe points such as burnt ground or a large area of non-burnable ground, such as a cricket or Australian rules football oval, or a large car park. This is achieved by attacking the fire from the flanks, or the rear, so that burnt ground is always nearby, and the fire is always in front of the firefighters. This avoids two disadvantages of attacking fires at the head of the fire where spot fires may start behind them or changes in wind behavior might accelerate the spread of the fire.

The result of several inquiries into firefighter death in Australian bushfires found that firefighters should stay out of the dead man zone and that they should always keep 250 liters of water in their truck for personal safety. This is now a standard operating procedure in the NSW Rural Fire Service, Country Fire Service and Country Fire Authority in Australia.
Answer: Firefighters can use burnt areas, car parks and sports areas to stay safe during a wildfire
Question: Why do people get married?
Answer: People get married for a variety of reasons. Most people get married because they feel like they are in love with the other person and want to spend the rest of their life with that person. Many people get married because they want to start a family. Some get married in order to have tax advantages and legal protection.
Question: What year was the car manufacturer Ferrari founded in?
Answer: Ferrari was founded in 1939 from the Alfa Romeo racing division as Auto Avio Costruzioni, the company built its first car in 1940, and produced its first Ferrari-badged car in 1947.