DataHammer/scimrc huggingface dataset:
Question: Whether multi-BERT shows transfer capability in their experiment?
Evidence: Table TABREF6 shows the result of different models trained on either Chinese or English and tested on Chinese. In row (f), multi-BERT is fine-tuned on English but tested on Chinese, which achieves competitive performance compared with QANet trained on Chinese. We also find that multi-BERT trained on English has relatively lower EM compared with the model with comparable F1 scores. This shows that the model learned with zero-shot can roughly identify the answer spans in context but less accurate. In row (c), we fine-tuned a BERT model pre-trained on English monolingual corpus (English BERT) on Chinese RC training data directly by appending fastText-initialized Chinese word embeddings to the original word embeddings of English-BERT. Its F1 score is even lower than that of zero-shot transferring multi-BERT (rows (c) v.s. (e)). The result implies multi-BERT does acquire better cross-lingual capability through pre-training on multilingual corpus. Table TABREF8 shows the results of multi-BERT fine-tuned on different languages and then tested on English , Chinese and Korean. The top half of the table shows the results of training data without translation. It is not surprising that when the training and testing sets are in the same language, the best results are achieved, and multi-BERT shows transfer capability when training and testing sets are in different languages, especially between Chinese and Korean.
In the lower half of Table TABREF8, the results are obtained by the translated training data. First, we found that when testing on English and Chinese, translation always degrades the performance (En v.s. En-XX, Zh v.s. Zh-XX). Even though we translate the training data into the same language as testing data, using the untranslated data still yield better results. For example, when testing on English, the F1 score of the model training on Chinese (Zh) is 53.8, while the F1 score is only 44.1 for the model training on Zh-En. This shows that translation degrades the quality of data. There are some exceptions when testing on Korean. Translating the English training data into Chinese, Japanese and Korean still improve the performance on Korean. We also found that when translated into the same language, the English training data is always better than the Chinese data (En-XX v.s. Zh-XX), with only one exception (En-Fr v.s. Zh-Fr when testing on KorQuAD). This may be because we have less Chinese training data than English. These results show that the quality and the size of dataset are much more important than whether the training and testing are in the same language or not.
It is not surprising that when the training and testing sets are in the same language, the best results are achieved, and multi-BERT shows transfer capability when training and testing sets are in different languages, especially between Chinese and Korean.
Answer: Yes. When training and testing sets are in different languages, especially between Chinese and Korean, the capability is shown.
Question: What are some ways in which I could use old books?
Answer: - Donate them to a charity 
- donate them to a prison 
- Sell them online
- Try origami with book pages 
- Hollow the books out and stick them together to create a storage unit 
- Cut the book covers and use it as bookmarks 
- Cut the book covers to create a collage 
- use the pages to create a wreath 
- sell them to a thrift store
Question: What is Pinot Grigio?
Evidence: Pinot Gris, Pinot Grigio (US: /ˈpiːnoʊ ˈɡriːdʒioʊ, -dʒoʊ/, UK: /ˈɡrɪdʒioʊ/) or Grauburgunder is a white wine grape variety of the species Vitis vinifera. Thought to be a mutant clone of the Pinot Noir variety, it normally has a grayish-blue fruit, accounting for its name, but the grapes can have a brownish pink to black and even white appearance. The word pinot could have been given to it because the grapes grow in small pinecone-shaped clusters. The wines produced from this grape also vary in color from a deep golden yellow to copper and even a light shade of pink, and it is one of the more popular grapes for skin-contact wine.

Pinot Gris is grown around the globe, with the "spicy" full-bodied Alsatian and lighter-bodied, more acidic Italian styles being most widely recognized. The Alsatian style, often duplicated in New World wine regions such as Marlborough, Tasmania, South Australia, Washington, Oregon, and South Africa tend to have moderate to low acidity, higher alcohol levels and an almost "oily" texture that contributes to the full-bodied nature of the wine. The flavors can range from ripe tropical fruit notes of melon and mango to some botrytis-influenced flavors. In Italy, Pinot grigio grapes are often harvested early to retain the refreshing acidity and minimize some of the overt-fruitiness of the variety, creating a more neutral flavor profile. This style is often imitated in other Old World wine regions, such as Germany, where the grape is known as Ruländer, or more commonly, Grauburgunder.
Answer: Pinot Gris, Pinot Grigio (US: /ˈpiːnoʊ ˈɡriːdʒioʊ, -dʒoʊ/, UK: /ˈɡrɪdʒioʊ/) or Grauburgunder is a white wine grape variety of the species Vitis vinifera. Pinot Gris is grown around the globe, with the "spicy" full-bodied Alsatian and lighter-bodied, more acidic Italian styles being most widely recognized.
Question: On what datasets are the comparison done?
Evidence: The proposed LID algorithm builds on the work in BIBREF8 and BIBREF26. We apply a naive Bayesian classifier with character (2, 4 & 6)-grams, word unigram and word bigram features with a hierarchical lexicon based classifier.
The naive Bayesian classifier is trained to predict the specific language label of a piece of text, but used to first classify text as belonging to either the Nguni family, the Sotho family, English, Afrikaans, Xitsonga or Tshivenda. The scikit-learn multinomial naive Bayes classifier is used for the implementation with an alpha smoothing value of 0.01 and hashed text features.
The lexicon based classifier is then used to predict the specific language within a language group. For the South African languages this is done for the Nguni and Sotho groups. If the lexicon prediction of the specific language has high confidence then its result is used as the final label else the naive Bayesian classifier's specific language prediction is used as the final result. The lexicon is built over all the data and therefore includes the vocabulary from both the training and testing sets.
The lexicon based classifier is designed to trade higher precision for lower recall. The proposed implementation is considered confident if the number of words from the winning language is at least one more than the number of words considered to be from the language scored in second place.
The stacked classifier is tested against three public LID implementations BIBREF17, BIBREF23, BIBREF8. The LID implementation described in BIBREF17 is available on GitHub and is trained and tested according to a post on the fasttext blog. Character (5-6)-gram features with 16 dimensional vectors worked the best. The implementation discussed in BIBREF23 is available from https://github.com/tomkocmi/LanideNN. Following the instructions for an OSX pip install of an old r0.8 release of TensorFlow, the LanideNN code could be executed in Python 3.7.4. Settings were left at their defaults and a learning rate of 0.001 was used followed by a refinement with learning rate of 0.0001. Only one code modification was applied to return the results from a method that previously just printed to screen. The LID algorithm described in BIBREF8 is also available on GitHub.
The stacked classifier is also tested against the results reported for four other algorithms BIBREF16, BIBREF26, BIBREF24, BIBREF15. All the comparisons are done using the NCHLT BIBREF7, DSL 2015 BIBREF19 and DSL 2017 BIBREF1 datasets discussed in Section SECREF2.
All the comparisons are done using the NCHLT [8], DSL 2015 [20] and DSL 2017 [2] datasets discussed in Section 2.
Answer: All the comparisons are done using the NCHLT, DSL 2015 and DSL 2017 datasets.
Question: What are the best selling albums of all time? Give me the list with the name of the artist and the name of the album
Answer: Best selling albums of all time:

- Michael Jackson: Thriller
- Eagles: Their Greatest Hits (1971–1975)
- Pink Floyd: The Dark Side of the Moon
- Whitney Houston / various artists: The Bodyguard
- Bee Gees / Various artists: Saturday Night Fever
- Fleetwood Mac: Rumours
- Eagles: Hotel California
- Shania Twain: Come On Over
- Meat Loaf: Bat Out of Hell
- AC/DC: Back in Black
Question: What are 3 popular dishes that can feed a large group of people?
Answer: Pizza is a popular dish that can be easily distributed. Hot dogs are also easy to make for a large group with the right equipment. Hamburgers are another common food when feeding a large crowd.
Question: Argue that large language models are not conscious.
Answer: Large language models weren't designed to be conscious, and so it seems unlikely that consciousness would emerge as an unintended side effect, or emergent property, of these models.
Question: How do people travel?
Answer: People travel from one place to another in various ways. The most common way is by walking, especially for short distances. Driving cars is a travel method for driving long distances such as to work or nearby cities. Bicycling is a popular travel method, especially for people that want exercise. Public transportation including buses and trains are used for traveling. Airplanes are used for long distances and international travel.
Question: Provide a dot point list of the last six artists that won a Grammy Award for Best Album. Include the title of the album and the year they won.
Answer: Here is a list of the last six artists that won a Grammy Award for Best Album.
- Harry Styles won for the album 'Harry's House' in 2023        
- Jon Batiste won for the album 'We Are' in 2022     
- Taylor Swift won for 'Folklore' in 2021    
- Billie Eilish won for 'When We All Fall Asleep, Where Do We Go?' in 2020       
- Kacey Musgraves won for the album 'Golden Hour' in 2019        
- Bruno Mars won for '24K Magic' in 2018
Question: What is Herd Immunity?
Answer: It’s a form of indirect protection from infectious disease that occurs when a large %age of a population has become immune to an infection, thereby providing a measure of protection for individuals who are not immune
Question: What is random access memory?
Answer: Random access memory (RAM) is a type of computer memory used to store data that can be accessed quickly. It is also known as dynamic random access memory (DRAM) and is used to store the instructions and data for a computer's operating system and applications. RAM is volatile memory, meaning it will lose its data if the power is turned off. It is also much faster than other types of memory such as hard disk drives and solid state drives.
Question: How many articles and sentences were used for the shared task?
Evidence: The input for both tasks consists of news articles in free-text format, collected from 36 propagandist and 12 non-propagandist news outlets and then annotated by professional annotators. More details about the data collection and the annotation, as well as statistics about the corpus can be found in BIBREF10, where an earlier version of the corpus is described, which includes 450 news articles. We further annotated 47 additional articles for the purpose of the shared task using the same protocol and the same annotators.
The training, the development, and the test partitions of the corpus used for the shared task consist of 350, 61, and 86 articles and of 16,965, 2,235, and 3,526 sentences, respectively. Figure FIGREF15 shows an annotated example, which contains several propaganda techniques. For example, the fragment babies on line 1 is an instance of both Name_Calling and Labeling. Note that the fragment not looking as though Trump killed his grandma on line 4 is an instance of Exaggeration_or_Minimisation and it overlaps with the fragment killed his grandma, which is an instance of Loaded_Language.
Table TABREF23 reports the total number of instances per technique and the percentage with respect to the total number of annotations, for the training and for the development sets.
The training, the development, and the test partitions of the corpus used for the shared task consist of 350, 61, and 86 articles and of 16,965, 2,235, and 3,526 sentences, respectively.
Answer: The training, the development, and the test partitions of the corpus used for the shared task consist of 350, 61, and 86 articles and of 16,965, 2,235, and 3,526 sentences, respectively.
Question: What is pan genomics?
Answer: Pan genomics is a concept introduced in 2005 by Tettelin and Medini which eventually took root in bioinformatics. Pan genome is the complete gene repertoire of a particular taxonomic group: although initially applied to closely related strains of a species, it can be applied to a larger context like genus, phylum, etc. It is divided in two parts- The Core genome: Set of genes common to all the genomes under study (These are often housekeeping genes vital for survival) and The Dispensable/Flexible Genome: Set of genes not present in all but one or some genomes under study. A bioinformatics tool BPGA can be used to characterize the Pan Genome of bacterial species.
Question: How does propose model model that capture three-way interactions?
Evidence: We model interactions between observations from the environment, goal, and document using layers. We first encode text inputs using bidirectional LSTMs, then compute summaries using self-attention and conditional summaries using attention. We concatenate text summaries into text features, which, along with visual features, are processed through consecutive layers. In this case of a textual environment, we consider the grid of word embeddings as the visual features for . The final output is further processed by MLPs to compute a policy distribution over actions and a baseline for advantage estimation. Figure FIGREF18 shows the model.
We model interactions between observations from the environment, goal, and document using layers. We first encode text inputs using bidirectional LSTMs, then compute summaries using self-attention and conditional summaries using attention. We concatenate text summaries into text features, which, along with visual features, are processed through consecutive layers. In this case of a textual environment, we consider the grid of word embeddings as the visual features for . The final output is further processed by MLPs to compute a policy distribution over actions and a baseline for advantage estimation. 
Answer: The answers are shown as follows:
*  We first encode text inputs using bidirectional LSTMs, then compute summaries using self-attention and conditional summaries using attention. We concatenate text summaries into text features, which, along with visual features, are processed through consecutive layers. In this case of a textual environment, we consider the grid of word embeddings as the visual features for . The final output is further processed by MLPs to compute a policy distribution over actions and a baseline for advantage estimation.
Question: From the given paragraph, write some points on Church.
Evidence: A church, church building or church house is a building used for Christian worship services and other Christian religious activities. The earliest identified Christian church is a house church founded between 233 and 256. From the 11th through the 14th centuries, there was a wave of church construction in Western Europe.

Sometimes, the word church is used by analogy for the buildings of other religions. Church is also used to describe the Christian religious community as a whole, or a body or an assembly of Christian believers around the world.
Answer: 1. A church, church building, or church house is a structure used for Christian religious activities such as worship ceremonies.
2. A home church that was established between 233 and 256 is the earliest known Christian congregation.
3. In Western Europe, there was a wave of church building from the 11th through the 14th centuries.
4. The word "church" is occasionally used as an analogy for the structures of other religions.
5. The word "church" is also used to refer to the global body of Christian believers as well as the Christian religious community as a whole.
Question: How many episodes in season one of Game of Thrones did Tim Van Patten direct?
Answer: Tim Van Patten directed the first two episodes of the first season of Game of Thrones: Winter is Coming and The Kingsroad.
Question: What is disadvantage of naive algorithm of simple random sampling?
Evidence: Several efficient algorithms for simple random sampling have been developed. A naive algorithm is the draw-by-draw algorithm where at each step we remove the item at that step from the set with equal probability and put the item in the sample. We continue until we have sample of desired size 
�
k. The drawback of this method is that it requires random access in the set.

The selection-rejection algorithm developed by Fan et al. in 1962 requires a single pass over data; however, it is a sequential algorithm and requires knowledge of total count of items 
�
n, which is not available in streaming scenarios.

A very simple random sort algorithm was proved by Sunter in 1977. The algorithm simply assigns a random number drawn from uniform distribution 
(
0
,
1
)
(0,1) as a key to each item, then sorts all items using the key and selects the smallest 
�
k items.

J. Vitter in 1985 proposed reservoir sampling algorithms, which are widely used. This algorithm does not require knowledge of the size of the population 
�
n in advance, and uses constant space.

Random sampling can also be accelerated by sampling from the distribution of gaps between samples and skipping over the gaps.
Answer: The drawback of this method is that it requires random access in the set.
Question: When was the United States Marine Corps founded?
Answer: On November 10, 1775, the Second Continental Congress meeting in Philadelphia passed a resolution stating that "two Battalions of Marines be raised" for service as landing forces with the fleet.  This resolution established the Continental Marines and marked the birth date of the United States Marine Corps.
Question: Which Game of Thrones season three episodes were directed by Michelle MacLaren?
Answer: She directed episodes 7 and 8, "The Bear and the Maiden Fair" and "Second Sons"
Question: Identify which car manufacturer is Chinese or American: BAIC, GMC
Answer: BAIC is Chinese, GMC is American
Question: What is the main cause of snow?
Answer: Snow forms when tiny ice crystals in clouds stick together to become snowflakes. If enough crystals stick together, they'll become heavy enough to fall to the ground. Snowflakes that descend through moist air that is slightly warmer than 0 °C will melt around the edges and stick together to produce big flakes.
Question: Who was Cleopatra's first husband
Answer: Ptolemy Dionysus – her brother
Question: What are some facts about Aydın İlter?
Evidence: Aydın İlter (1 July 1930 – 21 April 2022) was a Turkish general. He was General Commander of the Gendarmerie of Turkey (1993 – 1995) and previously served in the Special Warfare Department from 1963 to 1983, including as head of the Department from 1980 to 1983.
Answer: Aydın İlter was born on July 1st, 1930.  He as a Turkish General Commander of the Gendarmerie of Turkey from 1993 to 1995.  Prior to serving as General Commander he served in the Special Warfare Department from 1963 to 1983.  He was the head of that department from 1980 to 1983.  Aydın İlter died on April 21st, 2022 at the age of 91.
Question: Which Roman general was conspired against and assassinated that is quoted "Et tu, Brute?"?
Answer: Julius Cesar
Question: What is the plot of the movie going wild
Evidence: Going Wild is a 1930 Warner Brothers pre-Code comedy film based on the 1910 play The Aviator by James Montgomery and directed by William A. Seiter. The film stars many musical stars along with Joe E. Brown, Frank McHugh and Johnny Arthur.

A print is held in the Library of Congress collection.

Plot
Rollo Smith and his friend Jack Lane are down on their luck and have stowed away on a train, finding a place in the compartment of ace pilot and writer Robert Story. The conductor ejects Rollo and Jack from the train just where the famous writer is supposed to arrive, and Rollo is mistaken for Story.

Peggy Freeman and May Bunch both vie for Rollo's attention, believing that he is a famous pilot. The girls receive free room and meals at the Palm Inn. Rollo, who has never flown, is invited to fly in an air race as Story against a real aviator, "Ace" Benton, with a chance to win a $25,000 wager. After he somehow lifts the plane off the ground, Rollo can barely control the aircraft. Ferguson, the real pilot whom Peggy had locked in a closet, appears, but Rollo continues to unwittingly perform an aerial show, forcing Ace to abandon the race.

When Peggy accidentally pulls her parachute ring, Rollo joins her as they safely float to earth and he proposes.
Answer: Going Wild is a 1930 Warner Brothers pre-Code comedy film based on the 1910 play The Aviator by James Montgomery and directed by William A. Seiter. The film stars many musical stars along with Joe E. Brown, Frank McHugh and Johnny Arthur.

A print is held in the Library of Congress collection.

Rollo Smith and his friend Jack Lane are down on their luck and have stowed away on a train, finding a place in the compartment of ace pilot and writer Robert Story. The conductor ejects Rollo and Jack from the train just where the famous writer is supposed to arrive, and Rollo is mistaken for Story.

Peggy Freeman and May Bunch both vie for Rollo's attention, believing that he is a famous pilot. The girls receive free room and meals at the Palm Inn. Rollo, who has never flown, is invited to fly in an air race as Story against a real aviator, "Ace" Benton, with a chance to win a $25,000 wager. After he somehow lifts the plane off the ground, Rollo can barely control the aircraft. Ferguson, the real pilot whom Peggy had locked in a closet, appears, but Rollo continues to unwittingly perform an aerial show, forcing Ace to abandon the race.

When Peggy accidentally pulls her parachute ring, Rollo joins her as they safely float to earth and he proposes.
Question: Extract the population for Paris mentioned in the paragraph
Evidence: Paris (English: /ˈpærɪs/; French pronunciation: ​[paʁi] (listen)) is the capital and most populous city of France, with an official estimated population of 2,102,650 residents as of 1 January 2023 in an area of more than 105 km² (41 sq mi), making it the fourth-most populated city in the European Union as well as the 30th most densely populated city in the world in 2022. Since the 17th century, Paris has been one of the world's major centres of finance, diplomacy, commerce, fashion, gastronomy, and science. For its leading role in the arts and sciences, as well as its early and extensive system of street lighting, in the 19th century it became known as "the City of Light". Like London, prior to the Second World War, it was also sometimes called the capital of the world.
Answer: The official estimated population of Paris is 2,102,650 residents
Question: Think up of a bunch of different gifts you could give a teacher
Answer: An apple, a box of pencils, a giftcard, a card, a chocolate bar, school supplies, books
Question: Extract the family name of the fungus Clitocybe subcordispora.
Evidence: Clitocybe subcordispora is a rare species of agaric fungus in the family Tricholomataceae. Found in northern Europe, it was described as new to science in 1969 by Finnish mycologist Harri Harmaja. It is similar to species in the Clitocybe metachroa complex, but can be distinguished from them by its smaller spores, which measure 4.5–6.0 by 3.0–4.0 µm.
Answer: Tricholomataceae