DataHammer/scimrc huggingface dataset:
Question: Where can set theory be applied?
Evidence: Set theory is the branch of mathematical logic that studies sets, which can be informally described as collections of objects. Although objects of any kind can be collected into a set, set theory, as a branch of mathematics, is mostly concerned with those that are relevant to mathematics as a whole.

The modern study of set theory was initiated by the German mathematicians Richard Dedekind and Georg Cantor in the 1870s. In particular, Georg Cantor is commonly considered the founder of set theory. The non-formalized systems investigated during this early stage go under the name of naive set theory. After the discovery of paradoxes within naive set theory (such as Russell's paradox, Cantor's paradox and the Burali-Forti paradox) various axiomatic systems were proposed in the early twentieth century, of which Zermelo–Fraenkel set theory (with or without the axiom of choice) is still the best-known and most studied.

Set theory is commonly employed as a foundational system for the whole of mathematics, particularly in the form of Zermelo–Fraenkel set theory with the axiom of choice. Besides its foundational role, set theory also provides the framework to develop a mathematical theory of infinity, and has various applications in computer science (such as in the theory of relational algebra), philosophy and formal semantics. Its foundational appeal, together with its paradoxes, its implications for the concept of infinity and its multiple applications, have made set theory an area of major interest for logicians and philosophers of mathematics. Contemporary research into set theory covers a vast array of topics, ranging from the structure of the real number line to the study of the consistency of large cardinals.
Answer: Sets can be applied to virtually any application, given that the application can be represented via a logical set of mathematical objects.
Question: What is the goal of QC?
Evidence: Question classification (QC) deals with question analysis and question labeling based on the expected answer type. The goal of QC is to assign classes accurately to the questions based on expected answer. In modern system, there are two types of questions BIBREF0. One is Factoid question which is about providing concise facts and another one is Complex question that has a presupposition which is complex. Question Answering (QA) System is an integral part of our daily life because of the high amount of usage of Internet for information acquisition. In recent years, most of the research works related to QA are based on English language such as IBM Watson, Wolfram Alpha. Bengali speakers often fall in difficulty while communicating in English BIBREF1.
In this research, we briefly discuss the steps of QA system and compare the performance of seven machine learning based classifiers (Multi-Layer Perceptron (MLP), Naive Bayes Classifier (NBC), Support Vector Machine (SVM), Gradient Boosting Classifier (GBC), Stochastic Gradient Descent (SGD), K Nearest Neighbour (K-NN) and Random Forest (RF)) in classifying Bengali questions to classes based on their anticipated answers. Bengali questions have flexible inquiring ways, so there are many difficulties associated with Bengali QC BIBREF0. As there is no rich corpus of questions in Bengali Language available, collecting questions is an additional challenge. Different difficulties in building a QA System are mentioned in the literature BIBREF2 BIBREF3. The first work on a machine learning based approach towards Bengali question classification is presented in BIBREF0 that employ the Stochastic Gradient Descent (SGD).
The goal of QC is to assign classes accurately to the questions based on expected answer.
Answer: The goal of QC is to assign classes accurately to the questions based on expected answer.
Question: What are dilated convolutions?
Evidence: In this work we focus on end-to-end stateless temporal modeling which can take advantage of a large context while limiting computation and avoiding saturation issues. By end-to-end model, we mean a straight-forward model with a binary target that does not require a precise phoneme alignment beforehand. We explore an architecture based on a stack of dilated convolution layers, effectively operating on a broader scale than with standard convolutions while limiting model size. We further improve our solution with gated activations and residual skip-connections, inspired by the WaveNet style architecture explored previously for text-to-speech applications BIBREF10 and voice activity detection BIBREF9 , but never applied to KWS to our knowledge. In BIBREF11 , the authors explore Deep Residual Networks (ResNets) for KWS. ResNets differ from WaveNet models in that they do not leverage skip-connections and gating, and apply convolution kernels in the frequency domain, drastically increasing the computational cost.
Standard convolutional networks cannot capture long temporal patterns with reasonably small models due to the increase in computational cost yielded by larger receptive fields. Dilated convolutions skip some input values so that the convolution kernel is applied over a larger area than its own. The network therefore operates on a larger scale, without the downside of increasing the number of parameters. The receptive field $r$ of a network made of stacked convolutions indeed reads: $r = \sum _i d_i (s_i - 1),$
We explore an architecture based on a stack of dilated convolution layers, effectively operating on a broader scale than with standard convolutions while limiting model size.
Standard convolutional networks cannot capture long temporal patterns with reasonably small models due to the increase in computational cost yielded by larger receptive fields. Dilated convolutions skip some input values so that the convolution kernel is applied over a larger area than its own. The network therefore operates on a larger scale, without the downside of increasing the number of parameters.
Answer: Similar to standard convolutional networks but instead they skip some input values effectively operating on a broader scale.
Question: What are five channels for mass communications?
Answer: Mass communications involves sending single messages to large groups. Five examples of mass communication channels include television, radio, email, social media, and postal mails.
Question: Can you summarize for me in no more than three paragraphs the book, "The Little Engine That Could", by Watty Piper?
Evidence: The Little Engine That Could is an American folktale (existing in the form of several illustrated children's books and films) that became widely known in the United States after publication in 1930 by Platt & Munk. The story is used to teach children the value of optimism and hard work. Based on a 2007 online poll, the National Education Association listed the book as one of its "Teachers' Top 100 Books for Children"
Answer: The Little Engine That Could is a children's book written in 1930 by Watty Piper.  The main purpose of the book is to help bring out in children a positive, "can-do attitude."  The key phrase in the book is, "I think I can." 

The main character is the "Little Engine".  The Little Engine is an undersized locomotive that is called upon to pull rail cars full of good things for the boys and girls that live on the other side of the mountain.  Several other locomotives, appearing newer, stronger or more mature than the Little Engine all make excuses for why they will not help take the train cars over the mountain.

The Little Engine gladly takes on the task when called upon.  When starting to pull the heavy rail cars, The Little Engine strains with all its might and begins to say, "I think I can, I think I can, I think I can."  When climbing the mountain, it doesn't look like the Little Engine has the power to get over the peak.  The Little Engine puffs, "I think I can, I think I can, I think I can."  Finally The Little Engine reaches the top, comes over the crest and on the way down says, "I though I could, I thought I could, I thought I could."
Question: Within the hypothesis reranking approach what is suggested as the hypotheses?
Evidence: We take a hypothesis reranking approach, which is widely used in large-scale domain classification for higher scalability BIBREF13, BIBREF4. Within the approach, a shortlister, which is a light-weighted domain classifier, suggests the most promising $k$ domains as the hypotheses. We train the shortlister along with the added pseudo labels, leveraging negative system responses, and self-distillation, which are described in Section SECREF3. Then a hypothesis reranker selects the final prediction from the $k$ hypotheses enriched with additional input features, which is described in Section SECREF4.
We take a hypothesis reranking approach, which is widely used in large-scale domain classification for higher scalability [14, 5]. Within the approach, a shortlister, which is a light-weighted domain classifier, suggests the most promising k domains as the hypotheses.
Answer: The most promising k domains.
Question: In the anime Saint Seiya, who of the following characters is not the core 5 of the Bronze Saint Cloth: Pegasus Seiya, Dragon Shiryu, Cygnus Hyoga, Andromeda Shun, Phoenix Ikki, Aries Mu, Gemini Saga, Virgo Shaka
Answer: The core member of Saint Seiya's Bronze Saint Cloth are Pegasus Seiya, Dragon Shiryu, Cygnus Hyoga, Andromeda Shun, Phoenix Ikki. 

And Aries Mu, Gemini Saga, Virgo Shaka belong to the Gold Saints.
Question: What is the English football league system?
Answer: The English football league system, also known as the football pyramid, is a series of interconnected leagues for men's association football clubs in England, with five teams from Wales, one from Guernsey, one from Jersey and one from the Isle of Man also competing. The system has a hierarchical format with promotion and relegation between leagues at different levels, allowing even the smallest club the theoretical possibility of ultimately rising to the very top of the system, the Premier League. Below that are levels 2–4 organised by the English Football League, then the National League System from levels 5–10 administered by the FA, and thereafter feeder leagues run by relevant county FAs on an ad hoc basis.

The exact number of clubs varies from year to year as clubs join and leave leagues, merge, or fold altogether, but an estimated average of 15 clubs per division implies that more than 7,000 teams of nearly 5,300 clubs are members of a league in the English men's football league system.

As there are no official definitions of any level below 11, any references to the structure at level 12 and below should not be regarded as definitive.

The pyramid for women's football in England runs separately into ten tiers, and some England-based men's clubs play outside the English football league system.
Question: What TV show featured the Halliwell sisters that found they were witches that needed to battle demons and the forces of darkness?
Answer: The TV Show Charmed featured the Halliwell sisters as the Charmed ones that manifested their family witch powers to battle the source of Evil and the forces of darkness.
Question: What is a stinky slinky?
Answer: A stinky slinky is the nickname for a RV sewer hose. When emptying RV tanks an accordion-style hose is attached to the output port on the RV, with the other end being placed into a hole at a dump station. Levers are then pulled to empty the tanks: blank tank first (toilet contents), then gray tank after to remove any leftovers from when the black tank was emptied. Most people wear gloves when doing a tank dump. Given that the sewer hose is stretchy like a slinky, and removes toilet waste, the nickname “stinky slinky” is common.
Question: Have any women won the Nobel Prize in Physics?
Answer: Four women have won the Nobel Prize in Physics: Marie Skłodowska-Curie (1903), Maria Goeppert-Mayer (1963), Donna Strickland (2018), and Andrea Ghez (2020).
Question: True or false, fish live on land?
Answer: False.  Fish live in the water.
Question: Is there a Santa Claus and who is it?
Answer: While there was a Saint Nicholas who existed in history the current "Santa Claus" is a fictional character used as part of the celebration of Christmas.  

According to the narrative Santa Claus keeps a list of boys/girls and tracks to see who has been good and bad.  Based on this list he will fly around the world in a red sleigh pulled by reindeer.  As far as entering each home he will use a chimney if available or some other means.

The historical Saint Nicholas of Myra who was born around 270 A.D. has attributed to him the habit of secret gift giving to those in great need and not expecting it.  

Current western culture representations of "Santa Claus" have their roots in an ad campaign commissioned by Coca-Cola with art by Haddon Sundblom and debuting in the 1931 editions of the Saturday Evening Post and other magazines.
Question: Identify which instrument is string or percussion: Steelpan, Krar
Answer: Krar is string, Steelpan is percussion.
Question: In the series A Song of Ice and Fire, who is the founder of House Rowan?
Answer: Rowan Gold-Tree
Question: Identify which instrument is string or percussion: Bianzhong, Sorahi
Answer: Sorahi is string, Bianzhong is percussion.
Question: Provide a three sentence summary about the population of Kuçova.
Evidence: Currently the Kuçova district has a population of around 50,000. Of this population around 31,000 live in the city of Kuçova, classifying it as 12th of 65 municipalities on a national scale.[citation needed] Population density is 567 inhabitants/km2, which ranks the Kuçova district as the most heavily populated on a national scale. Another feature of this district compared with others in Albania is that city dwellers comprise 63% of the general population, the remainder living in villages nearby.
Answer: Kuçova has a population around 50,000 people. The approximate population density of the district is 567 inhabitants/km2. 63% of the population of Kuçova reside in the city.
Question: List the colors of the rainbow
Answer: Red, orange, yellow, green, blue, indigo, and purple
Question: Why was the European Union founded?
Answer: The European Union was founded by Belgium, France, Germany, Italy, Luxembourg and the Netherland in 1957. The goal of the European Union was to unite the national economies in Europe and to prevent future wars between the members states. To integrate the European economies further a single currency, the Euro, was introduced in 1999. Noways the European Union consists of 27 members, of which 20 have the Euro as official currency.
Question: When did the Post Office in Mission Beach first open?
Evidence: In the late 1920s after the construction of a road from El Arish, the area became a popular camping place. It was known as Mission Beach due to the mistaken belief that the Hull River Aboriginal Settlement previously located in the region was a religious mission. Mission Beach developed into a town during the 1940s and 50s with the Mission Beach Post Office opening on 15 December 1949.
Answer: Mission Beach Post Office opened on 15 December 1949.
Question: Classify each of the following as either a type of donut or a fruit candy brand: old-fashioned, Skittles, Mamba, maple bar, sprinkles, raised, Starburst, cruller, bear claw, apple fritter, Airheads
Answer: Donut: old-fashioned, maple bar, sprinkles, raised, cruller, bear claw, apple fritter
Fruit candy brand: Skittles, Mamba, Starburst, Airheads
Question: What is DevSecOps?
Evidence: DevSecOps is an augmentation of DevOps to allow for security practices to be integrated into the DevOps approach. Contrary to a traditional centralized security team model, each delivery team is empowered to factor in the correct security controls into their software delivery. Security practices and testing are performed earlier in the development lifecycle, hence the term "shift left" can be used. Security is tested in three main areas: static, software composition, and dynamic.

Checking the code statically via static application security testing (SAST) is white-box testing with special focus on security. Depending on the programming language, different tools are needed to do such static code analysis. The software composition is analyzed, especially libraries and their versions are checked against vulnerability lists published by CERT and other expert groups. When giving software to clients, licenses and its match to the one of the software distributed are in focus, especially copyleft licenses. Dynamic testing is also called black-box testing. The software is tested without knowing its inner functions. In DevSecOps it is on one hand called dynamically (DAST), or penetration testing. The goal is to catch, amongst others, errors like cross-site scripting, or SQL injection early. Threat types are for example published by the open web application security project, e.g. its TOP10. On the other hand, especially with microservices interactive application testing (IAST) is helpful to check which code is executed when running automated functional tests, the focus is to detect vulnerabilities within the applications. Contrary to SAST and DAST, IAST works inside the application.

DevSecOps has also been described as a cultural shift involving a holistic approach to producing secure software by integrating security education, secure by design, and security automation.
Answer: DevSecOps is an augmentation of DevOps with security integrated into the DevOps approach. It has been growing in recent years as producing secure software is becoming a top priority for companies.
Question: What book was the musical Hamilton based on?
Evidence: Hamilton is a sung-and-rapped-through musical with music, lyrics, and a book by Lin-Manuel Miranda, based on the 2004 book Alexander Hamilton by Ron Chernow. The musical tells the story of American Founding Father Alexander Hamilton. Composed over a seven-year period from 2008 to 2015, Miranda says Hamilton was originally a hip hop concept album in his head. The show draws heavily from hip hop, as well as R&B, pop, soul, and traditional-style show tunes. It casts non-white actors as the Founding Fathers of the United States and other historical figures. Miranda described Hamilton as about "America then, as told by America now."
Answer: Hamilton, the musical was based on the 2004 book Alexander Hamilton by Ron Chernow.
Question: What did the author conclude from the experiment?
Evidence: Our system was designed to cluster documents from a (potentially infinite) real-word data stream. The datasets typically used in the literature (TDT, Reuters) have a small number of clusters ( INLINEFORM0 20) with coarse topics (economy, society, etc.), and therefore are not relevant to the use case of media monitoring we treat - as it requires much more fine-grained story clusters about particular events. To evaluate our approach, we adapted a dataset constructed for the different purpose of binary classification of joining cluster pairs. We processed it to become a collection of articles annotated with monolingual and crosslingual cluster labels.
Statistics about this dataset are given in Table TABREF30 . As described further, we tune the hyper-parameter INLINEFORM0 on the development set. As for the hyper-parameters related to the timestamp features, we fixed INLINEFORM1 and tuned INLINEFORM2 on the development set, yielding INLINEFORM3 . To compute IDF scores (which are global numbers computed across a corpus), we used a different and much larger dataset that we collected from Deutsche Welle's news website (http://www.dw.com/). The dataset consists of 77,268, 118,045 and 134,243 documents for Spanish, English and German, respectively.
The conclusions from our experiments are: (a) the weighting of the similarity metric features using SVM significantly outperforms unsupervised baselines such as CluStream (Table TABREF35 ); (b) the SVM approach significantly helps to learn when to create a new cluster, compared to simple grid search for the optimal INLINEFORM0 (Table TABREF39 ); (c) separating the feature space into one for monolingual clusters in the form of keywords and the other for crosslingual clusters based on crosslingual embeddings significantly helps performance.
The conclusions from our experiments are: (a) the weighting of the similarity metric features using SVM significantly outperforms unsupervised baselines such as CluStream (Table 2); (b) the SVM approach significantly helps to learn when to create a new cluster, compared to simple grid search  for the optimal τ (Table 4); (c) separating the feature space into one for monolingual clusters in the form of keywords and the other for crosslingual clusters based on crosslingual embeddings signifi- cantly helps performance.
Answer: (a) the weighting of the similarity metric features using SVM significantly outperforms unsupervised baselines such as CluStream; (b) the SVM approach significantly helps to learn when to create a new cluster, compared to simple grid search  for the optimal τ; (c) separating the feature space into one for monolingual clusters in the form of keywords and the other for crosslingual clusters based on crosslingual embeddings signifi- cantly helps performance.
Question: Any masking or thresholding was used to evaluate DTS?
Evidence: Figure 9: Average expert per token during training, with 16 experts in each MoE layer
Answer: We use threshold to drop the experts whose weights fall below the threshold as Figure 1, and no extra communication or computation will be wasted. In Appendix, we show the curve of average experts per token during the training iterations, where the FLOPs of MoE-layers decrease quickly at the early stage. We have already added this missing detail to the paper now.
Question: Do all dog breeds have long tails?
Answer: Dogs naturally have a variety of tail lengths, ranging from long to short to stubs
Question: Do the authors identify any cultural differences in irony use?
Evidence: From a semantic perspective, despite the language and cultural differences between Arabic and French languages, CNN results show a high performance comparing to the other languages pairs when we train on each of these two languages and test on the other one. Similarly, for the French and English pair, but when we train on French they are quite lower. We have a similar case when we train on Arabic and test on English. We can justify that by, the language presentation of the Arabic and French tweets are quite informal and have many dialect words that may not exist in the pretrained embeddings we used comparing to the English ones (lower embeddings coverage ratio), which become harder for the CNN to learn a clear semantic pattern. Another point is the presence of Arabic dialects, where some dialect words may not exist in the multilingual pretrained embedding model that we used. On the other hand, from the text-based perspective, the results show that the text-based features can help in the case when the semantic aspect shows weak detection; this is the case for the $Ar\longrightarrow En$ configuration. It is worthy to mention that the highest result we get in this experiment is from the En$\rightarrow $Fr pair, as both languages use Latin characters. Finally, when investigating the relatedness between European vs. non European languages (cf. (En/Fr)$\rightarrow $Ar), we obtain similar results than those obtained in the monolingual experiment (macro F-score 62.4 vs. 68.0) and best results are achieved by Ar $\rightarrow $(En/Fr). This shows that there are pragmatic devices in common between both sides and, in a similar way, similar text-based patterns in the narrative way of the ironic tweets.
 Finally, when investigating the relatedness between European vs. non European languages (cf. (En/Fr)$\rightarrow $Ar), we obtain similar results than those obtained in the monolingual experiment (macro F-score 62.4 vs. 68.0) and best results are achieved by Ar $\rightarrow $(En/Fr). This shows that there are pragmatic devices in common between both sides and, in a similar way, similar text-based patterns in the narrative way of the ironic tweets.
Answer: No.