DataHammer/scimrc huggingface dataset:
Question: Do the improvement of Rouge scores over the original centroid method?
Evidence: Extractive multi-document summarization (MDS) aims to summarize a collection of documents by selecting a small number of sentences that represent the original content appropriately. Typical objectives for assembling a summary include information coverage and non-redundancy. A wide variety of methods have been introduced to approach MDS.
Many approaches are based on sentence ranking, i.e. assigning each sentence a score that indicates how well the sentence summarizes the input BIBREF0 , BIBREF1 , BIBREF2 . A summary is created by selecting the top entries of the ranked list of sentences. Since the sentences are often treated separately, these models might allow redundancy in the summary. Therefore, they are often extended by an anti-redundancy filter while de-queuing ranked sentence lists.
Other approaches work at summary-level rather than sentence-level and aim to optimize functions of sets of sentences to find good summaries, such as KL-divergence between probability distributions BIBREF3 or submodular functions that represent coverage, diversity, etc. BIBREF4 
The centroid-based model belongs to the former group: it represents sentences as bag-of-word (BOW) vectors with TF-IDF weighting and uses a centroid of these vectors to represent the whole document collection BIBREF5 . The sentences are ranked by their cosine similarity to the centroid vector. This method is often found as a baseline in evaluations where it usually is outperformed BIBREF0 , BIBREF6 .
This baseline can easily be adapted to work at the summary-level instead the sentence level. This is done by representing a summary as the centroid of its sentence vectors and maximizing the similarity between the summary centroid and the centroid of the document collection. A simple greedy algorithm is used to find the best summary under a length constraint.
In order to keep the method efficient, we outline different methods to select a small number of candidate sentences from each document in the input collection before constructing the summary.
We test these modifications on the DUC2004 dataset for multi-document summarization. The results show an improvement of Rouge scores over the original centroid method. The performance is on par with state-of-the-art methods which shows that the similarity between a summary centroid and the input centroid is a well-suited function for global summary optimization.
The summarization approach presented in this paper is fast, unsupervised and simple to implement. Nevertheless, it performs as well as more complex state-of-the-art approaches in terms of Rouge scores on the DUC2004 dataset. It can be used as a strong baseline for future research or as a fast and easy-to-deploy summarization tool.
The results show an improvement of Rouge scores over the original centroid method.
Answer: Yes, they do.
Question: Extract from the text the Australian city on which the show Bluey is inspired
Evidence: The show follows Bluey, an anthropomorphic six-year-old Blue Heeler puppy who is characterised by her abundance of energy, imagination and curiosity of the world. The young dog lives with her father, Bandit; mother, Chilli; and younger sister, Bingo, who regularly joins Bluey on adventures as the pair embark on imaginative play together. Other characters featured each represent a different dog breed. Overarching themes include the focus on family, growing up and Australian culture. The program was created and is produced in Queensland; the culture and lifestyle of Brisbane inspires the show's setting.
Answer: Brisbane
Question: Without quoting directly from the text tell me how Beppe Grillo died.
Evidence: On 7 December 1981 Grillo lost control of a Chevrolet K5 Blazer as he drove on a military road, forbidden to civilians, from Limone Piemonte to Colle di Tenda.
Answer: He died in a car accident
Question: What is the name of the gruff and tough female Viper pilot on the 2003 reboot of "Battlestar Galactica"?
Answer: Kara "Starbuck" Thrace
Question: What are four creative ways to use a chess set besides playing chess?
Answer: You could use the pieces to invent a different war game; you could create a bottle flipping game with the king and queen; if the pieces are wood, you could use them as kindling for a Bo fire; and you could use the pieces as decorative paper weights.
Question: Are you going for a walk today?
Answer: I am definitely going for a walk today, the weather is finally good! These last raining days haven't been the best, but now with this shinning sun, it would be a shame to just stay at home!
Question: Can you fish in the Kalamazoo river and lake in Allegan County?
Answer: Yes, the fishing in this waterway is very good.  There are an abundance of species of fish available year round whether ice fishing, shore fishing, or using a boat.  Large and small mouth bass, bluegill, perch, walleye, bowfin, steelhead, salmon, carp, muskie, northern pike, and catfish are all found swimming in these waters.
Question: Provide a list of cities you drive through to get from San Diego to Phoenix
Answer: Alpine, El Centro, Yuma, Gila Bend
Question: What were the baselines?
Evidence: To compare with our model, we select a number of strong summarization models as baseline systems. $\textsc {Lead-X}$ uses the top $X$ sentences as a summary BIBREF19. The value of $X$ is 3 for NYT and CNN/DailyMail and 1 for XSum to accommodate the nature of summary length. $\textsc {PTGen}$ BIBREF4 is the pointer-generator network. $\textsc {DRM}$ BIBREF10 leverages deep reinforcement learning for summarization. $\textsc {TConvS2S}$ BIBREF2 is based on convolutional neural networks. $\textsc {BottomUp}$ BIBREF11 uses a bottom-up approach to generate summarization. ABS BIBREF26 uses neural attention for summary generation. DRGD BIBREF27 is based on a deep recurrent generative decoder. To compare with our pretrain-only model, we include several unsupervised abstractive baselines: SEQ$^3$ BIBREF28 employs the reconstruction loss and topic loss for summarization. BottleSum BIBREF23 leverages unsupervised extractive and self-supervised abstractive methods. GPT-2 BIBREF7 is a large-scaled pretrained language model which can be directly used to generate summaries.
To compare with our model, we select a number of strong summarization models as baseline systems. $\textsc {Lead-X}$ uses the top $X$ sentences as a summary BIBREF19.
$\textsc {DRM}$ BIBREF10 leverages deep reinforcement learning for summarization. $\textsc {TConvS2S}$ BIBREF2 is based on convolutional neural networks. $\textsc {BottomUp}$ BIBREF11 uses a bottom-up approach to generate summarization. ABS BIBREF26 uses neural attention for summary generation. DRGD BIBREF27 is based on a deep recurrent generative decoder. To compare with our pretrain-only model, we include several unsupervised abstractive baselines: SEQ$^3$ BIBREF28 employs the reconstruction loss and topic loss for summarization. BottleSum BIBREF23 leverages unsupervised extractive and self-supervised abstractive methods. GPT-2 BIBREF7 is a large-scaled pretrained language model which can be directly used to generate summaries.
Answer: The answers are shown as follows:
* $\textsc {Lead-X}$
* $\textsc {PTGen}$
* $\textsc {DRM}$
* $\textsc {TConvS2S}$
*  $\textsc {BottomUp}$
* ABS
* DRGD
* SEQ$^3$
* BottleSum
* GPT-2
Question: If I have more pieces at the time of stalemate, have I won?
Evidence: Stalemate is a situation in chess where the player whose turn it is to move is not in check and has no legal move. Stalemate results in a draw. During the endgame, stalemate is a resource that can enable the player with the inferior position to draw the game rather than lose. In more complex positions, stalemate is much rarer, usually taking the form of a swindle that succeeds only if the superior side is inattentive.[citation needed] Stalemate is also a common theme in endgame studies and other chess problems.

The outcome of a stalemate was standardized as a draw in the 19th century. Before this standardization, its treatment varied widely, including being deemed a win for the stalemating player, a half-win for that player, or a loss for that player; not being permitted; and resulting in the stalemated player missing a turn. Stalemate rules vary in other games of the chess family.
Answer: No. 
Stalemate is a drawn position. It doesn't matter who has captured more pieces or is in a winning position
Question: Classify each of the following as a fast food or sit down restaurant: McDonalds, Subway, Chili's, Popeyes, Carrabbas, Domino's, Hooters
Answer: McDonalds: Fast Food Restaurant
Subway: Fast Food Restaurant
Chili's: Sit Down Restaurant
Popeyes: Fast Food Restaurant
Carrabbas: Sit Down Restaurant
Domino's: Fast Food Restaurant
Hooters: Sit Down Restaurant
Question: When I ski my legs form an A-frame shape and it doesn't look very nice, how can I fix this?
Answer: A-frame can occur due to many reasons, this includes improper boot setup, for example, the cuff alignment is incorrect, or technique issues. It is best to consult an experienced boot fitter to ensure the boot is set up correctly. Once you've ensured the boot is set up correctly, it is likely a technique issue. A common cause of A-frame is a result of rotating the outside knee inside more than the inside knee, and this can happen due to wider skis or wanting to create a bigger edge angle. Ideally, we should avoid over-rotating the knee inside as this creates a weaker position and instead rely on moving the hip and upper body into the inside of the turn to create a bigger edge angle and try to keep the outside leg relatively straight.

A good exercise to practice this is the T-drill, where you try to make sure your outside leg is as straight as possible and create edge angle by leaning your whole body into the turn, you'll need to shorten your inside leg by bringing your need to your chest, which will then still allow you to balance mostly on your straight downhill leg.
Question: How will chatGPT and other large language models effect education and engineering disciplines?
Answer: It is too early to tell how technologies like chatGPT will change industries, but people think that some portion of jobs will be replaced in education and engineering.  People also think that written tests and coding assignments for interviews will need to be refactored to reduce the chance that students or candidates can submit answers generated by large language models.
Question: What is Your Lie in April about?
Evidence: Fourteen-year-old piano prodigy, Kōsei Arima, becomes famous after winning several music competitions. When his mother Saki dies, Kōsei has a mental breakdown while performing at a piano recital; this results in him becoming unable to hear the sound of his piano, even though his hearing is otherwise unaffected.

Two years later, Kōsei has not touched the piano and views the world in monochrome. He does not focus on excelling in any activities and often spends time with his friends Tsubaki Sawabe and Ryōta Watari. Kōsei meets Kaori Miyazono, an audacious, free-spirited, fourteen-year-old violinist whose playing style reflects her manic personality. Kaori helps Kōsei return to playing the piano, and shows him his playing style can be free and groundbreaking. As Kaori continues to uplift Kōsei's spirits, he quickly realizes he loves her, although she seems to only be interested in Ryōta.

During a performance, Kaori, who later explains that she is anemic and needs routine testing, collapses and is hospitalized. She is later diagnosed with Aplastic Anemia. She invites Kōsei to play with her at a gala but she does not arrive. Her health deteriorates and she becomes dejected. Kōsei plays a duet with a friend, which motivates Kaori to attempt a risky and potentially deadly surgery so she may possibly play with Kosei once more. While playing in the finals of the Eastern Japan Piano Competition, Kōsei sees Kaori's spirit accompanying him and realizes she has died during the surgery.

At her funeral, Kaori's parents give Kōsei a letter from Kaori that reveals she was aware of her impending death and became more free-spirited, both as a person and in her music, so she would not take her regrets to Heaven. She confesses she had been in love with Kōsei's piano playing since watching him perform at a concert when she was five. This inspired her to play the violin so she could play with him one day. Kaori fabricated her feelings towards Ryōta so she could get closer to Kōsei without hurting Tsubaki, who harbored affection for Kōsei. She then confesses her love for him. Tsubaki comforts Kōsei and tells him she will be by his side. Kaori also leaves behind a picture of herself as a child, coming back from the concert that inspired her, with Kōsei in the background. Kōsei later frames this picture.
Answer: Your Lie in April is a manga and an anime about friendship through music. The protagonist Kosei Arima is a very talented piano prodigy who goes through a mental breakdown from the pressure of performing and becomes deaf to the sound of his own piano. The world becomes monotonous and depressing until he meets Kaori Miyazono, a free-spirited violinist who reminds him of how to play music freely again. However, Kaori suffers from anemia and often has to go to the hospital. Despite this, the two often play together and Kosei falls in love. Kaori passes away soon after and leaves a letter for Kosei explaining how she loved him back and his piano playing. Kosei uses this as inspiration to get back into music and play freely once more.
Question: What are the words of House Karstark?
Answer: "The Sun of Winter"
Question: What type of weather is typically associated with the desert?
Answer: The desert is known for being very hot and very dry
Question: What do players of American football wear helmets? Write the response as if your are an American explaining to a coworker from another country.
Answer: American football is a high impact sport where injuries such as concussions are very common. The helmet is meant to lesson the occurrence of traumatic brain injuries like concussions by providing padding to the skull. The helmet is hard shell on the outside with soft padding on the inside. Players are required to wear them anytime they are on the field of play. Helmets were originally made of leather but over the years improvements have been made to better protect players.
Question: What is the California Alpine Club?
Answer: The California Alpine Club (CAC) is a membership club with overnight lodges on Mount Tamalpais in Mill Valley, CA and at Echo Lake, which is 20 minutes outside of South Lake Tahoe.
Question: Using the following text, extract the last 3 CEO's. Place them in a bullet list in order of current to least current.
Evidence: Governors/Chief Executive Officers
The following individuals have been appointed to serve as chief executive of the Commonwealth Bank of Australia, or precursor titles:

Order	Name	Title	Term start	Term end	Time in office
1	Sir Denison Miller KCMG	Governor	June 1912	June 1923	11 years, 29 days
2	James Kell	June 1923	October 1926	3 years, 122 days
3	Sir Ernest Riddle	October 1926	February 1938	11 years, 121 days
4	Sir Harry Sheehan CBE	March 1938	March 1941	3 years, 0 days
5	Hugh Traill Armitage CMG	July 1941	December 1948	7 years, 183 days
6	Dr H. C. Coombs	January 1949	January 1960	11 years, 0 days
7	Ernest Richardson CBE	Managing Director	January 1960	March 1965	5 years, 89 days
8	Sir Bede Callaghan CBE	May 1965	August 1976	11 years, 92 days
9	Sir Ronald Elliott	August 1976	August 1981	5 years, 0 days
10	Vern Christie AO	August 1981	March 1987	5 years, 212 days
11	Donald Sanders AO CB	March 1987	December 1990	3 years, 275 days
Chief Executive Officer	January 1991	June 1992	1 year, 181 days
12	David Murray AO	June 1992	September 2005	13 years, 92 days
13	Sir Ralph Norris KNZM	September 2005	November 2011	6 years, 29 days
14	Ian Narev	December 2011	April 2018	11 years, 119 days
15	Matt Comyn	April 2018	incumbent	4 years, 355 days
Answer: * Matt Comyn - Current / Incumbent since April 2018
* Ian Narev - December 2011 to April 2018
* Sir Ralph Norris KNZM - September 2005 to November 2011
* David Murray AO - June 1992  to September 2005
Question: Classify the following movies as either Comedy or Horror: Weekend at Bernie's, Scream, What Lies Beneath, Happy Gilmore, Cujo, Billy Madison, Kingpin, Carrie, Halloween, Encino Man, Misery
Answer: Weekend at Bernie's: Comedy
Scream: Horror
What Lies Beneath: Horror
Happy Gilmore: Comedy
Cujo: Horror
Billy Madison: Comedy
Kingpin: Comedy
Carrie: Horror
Halloween: Horror
Encino Man: Comedy
Misery: Horror
Question: What is a Profit and loss account in finance?
Answer: A profit and loss account shows the money a business has earned from selling goods and
services, less the money spent on goods, services and overheads.
Question: Why are people migrating in the US from the NE and Mid-West to the South and SE?
Answer: better weather year round
Question: Compared to a human, categorize the following as fast or slow animals: sloth, cheetah, eagle, tortoise, hippo, slug, horse.
Answer: A sloth, tortoise and slug are all slower than a sprinting human. If traveling at top speed, a cheetah, eagle, hippo, and horse are all faster than a sprinting human.
Question: Which of the following are weather events: rain, snow, sleet, sunshine, hail, tornadoes, hurricanes, trees, lightening, rocks?
Answer: Rain, snow, sleet, sunshine, hail, tornadoes, hurricanes, and lightening are weather events. Trees and rocks are not weather events.
Question: Which one of the four proposed models performed best?
Evidence: We employ several complementary metrics to capture different aspects of the model. The F1 results are shown in Table TABREF24. Among all single models, LFT performs the best, followed by MinAvgOut. RL is also comparable with previous state-of-the-art models VHRED (attn) and Reranking-RL. We think that this is because LFT exerts no force in pulling the model predictions away from the ground-truth tokens, but rather just makes itself aware of how dull each response is. Consequently, its responses appear more relevant than the other two approaches. Moreover, the hybrid model (last row) outperforms all other models by a large margin. One might expect that minimizing AVGOUT causes the models to move further away from the ground-truth tokens, so that it will hurt relevance. However, our F1 results show that as the responses become more diverse, they are more likely to include information more related and specific to the input contexts, which actually makes the model gain on both diversity and relevance. This will be further confirmed by the output examples in Table TABREF29.
Among all single models, LFT performs the best, followed by MinAvgOut. RL is also comparable with previous state-of-the-art models VHRED (attn) and Reranking-RL. We think that this is because LFT exerts no force in pulling the model predictions away from the ground-truth tokens, but rather just makes itself aware of how dull each response is. Consequently, its responses appear more relevant than the other two approaches. Moreover, the hybrid model (last row) outperforms all other models by a large margin. 
Answer: the hybrid model MinAvgOut + RL
Question: Who is Santa Clause?
Answer: Santa Clause is known as Father Christmas or Saint Nicholas in Christian culture.  According to the myth Santa Clause rides a slay and brings presents to all the children all over the world during Christmas every year.  Santa Clause lives at the North Pole with the elves.  When he is not busy delivering presents he and the elves are hard work at the North Pole making presents for the following year.  Christian families let their kids believe this myth until they are at a reasoning age and can figure out for themselves that Santa Clause is not real.
Question: Classify each of the following as either a natural hair color or a grocery store bakery brand: Hostess, blonde, brunette, Betty Crocker, Pilsbury, red, black, Entenmann's
Answer: Natural hair color: blonde, brunette, red, black
Grocery store bakery brands: Hostess, Betty Crocker, Pilsbury, Entenmann's
Question: Name the largest cities in Canada
Answer: The largest cities in Canada by population are Toronto, Montreal and Vancouver. Toronto has a population of 5.6 million, Montreal has a population of 3.6 million and Vancouver has a population of 2.4 million.
Question: They can visualize the relationship between languages in the multilingual space by what?
Evidence: By means of cross-entropy, we can also visualize the relation between languages in the multilingual space. Figure FIGREF12 plots the interpolation results for two relatively dissimilar languages, English and German. As expected, once the language vector moves too close to the German one, model performance drops drastically.
More interesting results can be obtained if we interpolate between two language variants and compute cross-entropy of a text that represents an intermediate form. fig:eng-enm shows the cross-entropy of the King James Version of the Bible (published 1611), when interpolating between Modern English (1500–) and Middle English (1050–1500). The optimal point turns out to be close to the midway point between them.
By means of cross-entropy, we can also visualize the relation between languages in the multilingual space.
Answer: Cross-entropy.
Question: Describe the perfect weekend trip to Boston, Massachusetts.
Answer: The best way to spend a weekend in Boston is walking the Freedom Trail in Downtown Boston. Seeing a Red Sox game at Fenway Park is practically required, and if visiting in the off-season, taking a tour of the stadium will suffice. You need to have a lobster roll at the Union Oyster House for Lunch. You should have a cannoli from Mike's Pastry in the North End for dessert as they are the best. Take the T from Government Center to the MFA stop to visit the Museum of Fine Arts. You should stay at the XV Beacon Hotel by the Boston Common. The Boston Commons is a lovely place to have a picnic as well.
Question: What are the names of the three largest United States Virgin Islands?
Answer: St. Croix, St. John, and St. Thomas.