DataHammer/scimrc huggingface dataset:
Question: Should their approach be applied only when dealing with incomplete data?
Evidence: Experimental results for the Twitter Sentiment Classification task on Kaggle's Sentiment140 Corpus dataset, displayed in Table TABREF37, show that our model has better F1-micros scores, outperforming the baseline models by 6$\%$ to 8$\%$. We evaluate our model and baseline models on three versions of the dataset. The first one (Inc) only considers the original data, containing naturally incorrect tweets, and achieves accuracy of 80$\%$ against BERT's 72$\%$. The second version (Corr) considers the corrected tweets, and shows higher accuracy given that it is less noisy. In that version, Stacked DeBERT achieves 82$\%$ accuracy against BERT's 76$\%$, an improvement of 6$\%$. In the last case (Inc+Corr), we consider both incorrect and correct tweets as input to the models in hopes of improving performance. However, the accuracy was similar to the first aforementioned version, 80$\%$ for our model and 74$\%$ for the second highest performing model. Since the first and last corpus gave similar performances with our model, we conclude that the Twitter dataset does not require complete sentences to be given as training input, in addition to the original naturally incorrect tweets, in order to better model the noisy sentences.
We evaluate our model and baseline models on three versions of the dataset. The first one (Inc) only considers the original data, containing naturally incorrect tweets, and achieves accuracy of 80$\%$ against BERT's 72$\%$. The second version (Corr) considers the corrected tweets, and shows higher accuracy given that it is less noisy. 
Answer: No.
Question: Give me a list of pros and cons of buying a bigger house
Answer: Buying a bigger house is a major life decision involving many factors. Pros include
- room for more people, especially helpful if you’re growing a family or you like to host 
- room for gear such as exercise equipment or a spa
- bigger homes may include more land which can provide solitude and a larger area for various outdoor activities 

Cons include
- bigger homes may be more expensive to purchase 
- bigger homes may be more challenging to maintain and clean
Question: What makes a healthy diet?
Answer: A healthy diet is one composed of an appropriate amount of calories balanced across macronutrients with clean sources of fruits, vegetables, grains, and other foods. An adult should generally target around 2000 calories per day, however this number should be greater depending on age, size, and activity level. Processed foods are generally less healthy and are associated with risk of diseases including heart disease and diabetes.
Question: Give me multiple modes of transport to get to Australia
Answer: Fly by plane, take a boat or cruise ship, swim, paddle board, kayak, sail
Question: Write a short story about a person who discovers a hidden room in their house. The story should include a plot twist and a clear resolution at the end.
Answer: Alice was a housewife living in a small suburban town. One day, she was looking around her house and noticed a small door near the back of the garage. Curious, she opened the door and stepped into a hidden room. She was amazed to find that it was filled with books and other items that were locked away in the room. Alice was fascinated and started to explore the room, reading the books and looking at the items. 

She soon realized that the room was actually a secret passageway that connected the garage to a secret underground city. Alice was amazed to find out that the city was filled with all sorts of strange and magical creatures, hidden away from the rest of the world. She spent days exploring the city and learning more about the magical creatures. Eventually, she was able to return home and share her discovery with the rest of her family. 

Alice's discovery of the secret city and the magical creatures was a life-changing experience for her and her family. It was a truly magical moment that changed the course of her life.
Question: Which is a bird or fish: Black grouse, Blackfish
Answer: Black grouse is a bird, Blackfish is a fish
Question: When does human life begin?
Answer: Causation theory is applied to the question of the point at which human life begins. It is concluded that the potential human being becomes actualized through the cessation of an exclusive in-utero dependency upon the material, formal, and efficient causes of its being, and the beginning of a nonexclusive ex-utero dependency upon nurturing and care-giving sources.
Question: From the given text, Provide me step by step instructions on how to prepare tea.
Evidence: Steeping, or brewing, is the process of making tea from leaves and hot water, generally using 2 grams (0.071 oz) of tea per 100 millilitres (3.5 imp fl oz; 3.4 US fl oz) of water (H2O) or about 1 teaspoon of green tea per 150 ml cup. Steeping temperatures range from 61 °C (142 °F) to 87 °C (189 °F) and steeping times from 30 seconds to three minutes.
Answer: 1. To brew/steep tea, use 2gm tea leaves per 100ml of water and let it brew between 61 °C to 87 °C for 30 seconds to 3 minutes.
2. For green tea, use 1 teaspoon of green tea per 150 ml of water and  let it brew between 61 °C to 87 °C for 30 seconds to 3 minutes.
Question: What does "Eq (3) is renormalized" mean?
Evidence: While ray marching in Eq. (1) allows computing the ray color, we are also interested in finding the distribution of distances that give rise to this color-this will allow using depths in RGB-D data for supervision. To this end, we show that Eq. (1) derives from an inhomogenous spatial Poisson process.
Consider a ray r(t) = x 0 + dt traveling through a camera at position x 0 along direction d. The probability that light originating at point r(t) will not scatter and reach the camera unimpeded (transmittance) is equal to the probability that no events occur in the spatial Poisson process T (t) = exp (− t 0 σ(r(t ))dt ). NeRF does not model light sources explicitly, but assumes that lighting conditions are expressed by the color value of each point. As a result, the light emitted at the point r(t) in the direction of the camera −d has the color c(r(t), d), and its intensity is proportional to the density of particles σ(r(t)) at that point. Consequently, the amount of light reaching the camera from r(t) is proportional to
(2)
In fact, under mild assumptions, p(t) is exactly equal to the distribution of possible depths t at which the observed colors originated 2 . We provide the full derivation in Appendix B.1.
We can now reframe Eq. (1) as the expected color value under the depth distribution p(t):
Typically, one chooses a maximum render distance t far as the upper bound for the integration interval. This leaves the probability p(t > t far ) = T (t far ) that light from beyond t far is missed. To account for that, Eq. () is renormalized by dividing by T (t far ) after approximating it with samples 0 ≤ t i ≤ t far .
Typically, one chooses a maximum render distance tfar as the upper bound for the integration interval. This leaves the probability p(t > tfar) = T(tfar) that light from beyond tfar is missed. To account for that, Eq. (3) is renormalized by dividing by T(tfar) after approximating it with samples 0 ≤ ti ≤ tfar.
Answer: By renormalization we mean that estimates for p(t) will be divided by the transmittance of the ray in the sampled interval T(t_{\text{far}}) = p(t < t_{\text{far}}), such that they add to one. We will clarify in the revision.
Question: Classify the following based on what kind of animals they are.
rodentia, chiroptera, lizards, primates, crocodiles, soricomorpha, turtles, snakes
Answer: Reptiles- lizards, crocodiles, turtles, snakes
Mammals- rodentia, chiroptera, soricomorpha, primates
Question: What are the common captioning metrics?
Evidence: We trained and evaluated our algorithm on the Microsoft COCO (MS-COCO) 2014 Captions dataset BIBREF21 . We report results on the Karpathy validation and test splits BIBREF8 , which are commonly used in other image captioning publications. The dataset contains 113K training images with 5 human annotated captions for each image. The Karpathy test and validation sets contain 5K images each. We evaluate our models using the CIDEr-D BIBREF22 , SPICE BIBREF23 , BLEU BIBREF24 , METEOR BIBREF25 , and ROUGE-L BIBREF26 metrics. While it has been shown experimentally that BLEU and ROUGE have lower correlation with human judgments than the other metrics BIBREF23 , BIBREF22 , the common practice in the image captioning literature is to report all the mentioned metrics.
We trained and evaluated our algorithm on the Microsoft COCO (MS-COCO) 2014 Captions dataset BIBREF21 . We report results on the Karpathy validation and test splits BIBREF8 , which are commonly used in other image captioning publications. The dataset contains 113K training images with 5 human annotated captions for each image. The Karpathy test and validation sets contain 5K images each. We evaluate our models using the CIDEr-D BIBREF22 , SPICE BIBREF23 , BLEU BIBREF24 , METEOR BIBREF25 , and ROUGE-L BIBREF26 metrics. While it has been shown experimentally that BLEU and ROUGE have lower correlation with human judgments than the other metrics BIBREF23 , BIBREF22 , the common practice in the image captioning literature is to report all the mentioned metrics.
Answer: The answers are shown as follows:
* the CIDEr-D BIBREF22 , SPICE BIBREF23 , BLEU BIBREF24 , METEOR BIBREF25 , and ROUGE-L BIBREF26 metrics
Question: Which is the best tube line?
Answer: The London Underground has many lines that are popular for different reasons. The Victoria line is one of the fastest with the most convenient stops although it is noisy and lacks air conditioning. The Hammersmith, Metropolitan and Circle line have air conditioning making them popular in summer. Although not technically part of the London Underground, the Docklands Light Railway has a very scenic route when viewed from the front seats of the driverless trains. The Elizabeth Line is also popular, although technically not an underground line, due to it's new trains, stunning station architecture and faster routes.
Question: What number octane gas should be used for combustion engines in vehicles?
Answer: Manufacturers list the minimal octane to be used on specific vehicles in the owners manual. Always check the manual to be sure the proper fuel is being used. An octane number such as 87, 91, 93 indicates the amount of heat tolerance of the fuel before igniting inside the engine cylinder. The higher the octane number, the higher heat tolerance. If you use the wrong octane in a vehicle, such as using 87, rather than 93 for a high performing turbo or supercharged vehicle, the engine could produce knock or pre-detonation. Knock occurs when the timing of of the air and fuel mixture in the cylinder explodes too early and can cause serious damage to the engine components. Knock is also something you can hear and feel and can be noticed by the driver. Having the detonation of the air and fuel, produced by the spark plug that is intended from the factory is optimal for the longevity of the vehicle.
Question: What are the expansions of FraCaS?
Evidence: The FraCaS test suite is an NLI data set consisting of 346 inference problems. Each problem contains one or more premises followed by one yes/no-question. There is a three way classification: YES, NO or UNK (unknown, see Figure 1 for an example from FraCaS). The FraCaS test suite was later on turned into machine-readable format by Bill McCartney
Expansions of FraCaS include: a) MultiFraCaS, in effect a multilingual FraCaS, and b) JSem, the Japanese counterpart to FraCaS, which expands the original FraCaS in a number of ways.
Even though the FraCaS test suite contains a rather small number of examples (346), it covers a lot of NLI cases and is, at least to some extent, multilingual. It is to some extent precise, even though there are test cases that do not involve a clear answer and thus are dubbed as undefined in Bill MacCartney's XML version. A further drawback of the FraCaS test stuite is that it involves constructed examples, rather than real text.
An UNK example from the FraCaS test suite.
A Scandinavian won the Nobel Prize.
Every Swede is Scandinavian.
Did a Swede win the Nobel prize?
A Swede won the Nobel prize.
UNK [FraCaS 065]
Expansions of FraCaS include: a) MultiFraCaS, in effect a multilingual FraCaS5 , and b) JSem, the Japanese counterpart to FraCaS, which expands the original FraCaS in a number of ways.
Answer: a) MultiFraCaS, in effect a multilingual FraCaS5 , and b) JSem, the Japanese counterpart to FraCaS, which expands the original FraCaS in a number of ways.
Question: Extract the reason why Anderson got the nickname 'Slow Mo'
Evidence: Anderson plays at a deliberate pace, and he is not as fast as more athletically gifted players. Popovich stated that he is "not what you’d call a typical NBA athlete". However, Anderson is praised for his basketball IQ. He is able to change speeds and fake out his opponents to keep them off balance. His methodical style earned him the nickname "Slow Mo" in eighth grade in AAU, and the name has stuck with him. "[He] really understands how to use his speed—he's not super fast, but he's super bright and really knows how to use angles," said Kevin Boyle, who coached Anderson on the national team in 2012. USA Today described him as "languid but quick enough to lead the fast break". Anderson's defense was considered a weakness. In college, his teams usually played zone as he struggled containing smaller, quicker guards while playing man-to-man. His defense improved with the Spurs in 2017–18, when he guarded both forward positions while leveraging his wingspan and instincts. Against quicker small forwards, he uses his physicality to keep players off balance.
Answer: The reason is because Anderson plays at a deliberate pace, slower than most other peer players, while being able to use his high basketball IQ to change speeds and fake out his opponents on the court.
Question: Which is the windiest continent on Earth?
Answer: Antarctica is the windiest continent on Earth. Cold air rushes downhill from the center of the continent toward the sea in all directions.
Question: Can you provide a clarification on grid-search of LCCS parameters in initialization stage?
Evidence: The overall objective of the proposed method is to finetune LCCS parameters to minimize crossentropy loss on the support samples:
where x and y are input and one-hot class encoding of target domain support samples L spt , and f is the source model with learnable LCCS parameters. The proposed method comprises an initialization and a gradient update stage.
Initialization stage: We search for initialization values for LCCS to warm start the optimization process. We first compute the support BN statistics µ spt and σ spt by exponential moving average (EMA) for m epochs, which allows µ spt and σ spt to update smoothly. Then, we conduct a onedimensional grid search on the LCCS parameters by setting η spt,i = ρ spt,i = v for i ∈ {1, . . . , n} where v ∈ {0, 0.1, . . . , 1.0} and η s = ρ s = 1 − v with values tied across all BN layers. The initialization value that minimizes cross-entropy loss on the support samples is selected.
We further optimize the LCCS parameters by gradient descent update for m epochs while concurrently updating support BN statistics by EMA. In this stage, parameter values are not tied across BN layers and we do not impose convex constraint on the training and support coefficient pairs to allow more diverse combinations.
We set m = 10 for both stages for all our experiments. Support samples are augmented with the same data augmentations for source model training.
We set m = 10 for both stages for all our experiments. Support samples are augmented with the same data augmentations for source model training.
Answer: We use the same few-shot support set throughout the adaptation stage i.e. we do not reserve additional validation set due to limited number of support samples. As stated in Section 3.3, we augment support samples with the same source data augmentations to increase diversity.
Question: When is the best time to see cherry blossom in Japan?
Answer: The best time to visit Japan for cherry blossoms is around late March through early May, depending on the prefecture.  There are a number of factors that influene when the blooming will take place each year such as temperature and rain.
Question: Does the dataset they use differ from the one used by Pasupat and Liang, 2015?
Evidence: Dataset: For training and testing we use the train-validation-test split of WikiTableQuestions BIBREF0 , a dataset containing 22,033 pairs of questions and answers based on 2,108 Wikipedia tables. This dataset is also used by our baselines, BIBREF0 , BIBREF3 . Tables are not shared across these splits, which requires models to generalize to unseen data. We obtain about 3.8 million training triples $(q,t,l)$ , where $l$ is a binary indicator of whether the logical form gives the correct gold answer when executed on the corresponding table. 76.7% of the questions have at least one correct candidate logical form when generated with the model of BIBREF0 .
For training and testing we use the train-validation-test split of WikiTableQuestions BIBREF0 , a dataset containing 22,033 pairs of questions and answers based on 2,108 Wikipedia tables. This dataset is also used by our baselines, BIBREF0 , BIBREF3 .
Answer: No.
Question: If you had to survive on a deserted island by yourself for a month, classify these items as 'useful' or 'not useful'.
Answer: axe, phone, pen, rope, lighter, fishing rod, makeup
Question: Give me a brief summary of the spanish civil war
Evidence: The Spanish Civil War broke out in 1936: on 17 and 18 July, part of the military carried out a coup d'état that triumphed in only part of the country. The situation led to a civil war, in which the territory was divided into two zones: one under the authority of the Republican government, that counted on outside support from the Soviet Union and Mexico (and from International Brigades), and the other controlled by the putschists (the Nationalist or rebel faction), most critically supported by Nazi Germany and Fascist Italy. The Republic was not supported by the Western powers due to the British-led policy of non-intervention. General Francisco Franco was sworn in as the supreme leader of the rebels on 1 October 1936. An uneasy relationship between the Republican government and the grassroots anarchists who had initiated a partial Social revolution also ensued.


Republican volunteers at Teruel, 1936
The civil war was viciously fought and there were many atrocities committed by all sides. The war claimed the lives of over 500,000 people and caused the flight of up to a half-million citizens from the country. On 1 April 1939, five months before the beginning of World War II, the rebel side led by Franco emerged victorious, imposing a dictatorship over the whole country. Thousands of men and women were imprisoned after the civil war in Francoist concentration camps, with approximately 367,000 to 500,000 prisoners being held in 50 camps or prisons.
Answer: The Spanish Civil War started on the 17th and 18th of July 1936 due to a coup d'etat by the military that divided the country into two zones, one side led by the republican government, the other controlled by the putschists (nationalists). The war claimed 500,000 lives and caused a mass exodus of up to 500,000 more. It ended on the 1st of April 1939 with the nationalists taking control of the country, imposing a dictatorship led by General Franco.
Question: What country has the most all time medals at the Winter Olympics?
Answer: Norway leads the all time medal count for the winter olympics
Question: What are some easy and tasty dinner recipes I can make tonight?
Answer: One easy and tasty dinner you can make is beef or fish tacos. You can assemble tortillas and toppings like cheese, sour cream, avocado, and onions.
Another easy dinner is baked fish with vegetables, of which there are lots of variations. You can make baked salmon with asparagus or baked tilapia with brussels sprouts.
Finally, pasta can be an easy and tasty dinner. Simply choose your pasta shape, a jar of pasta sauce, and a protein and some veggies to toss into the sauce.
Question: What kind of bacteria is Bifidobacterium thermacidophilum
Answer: Bifidobacterium thermacidophilum is a Gram-positive, rod-shaped species of bacteria. Strains of this species were originally isolated from an anaerobic digester used to treat wastewater from a tofu farm. The species is thermophilic and can grow at a temperature of 49.5 °C.

Strains of B. thermacidophilum have been experimentally used as probiotics. It was effective in reducing damage to the gut in a mouse model of E. coli infection.

B. thermacidophilum has been divided into two subspecies: subsp. Porcinum and subsp. Thermacidophilum.
Question: What's the most impressive thing happened in the world since you were born?
Answer: The day that I was born is just like yesterday and the most impressive thing I saw is that people never learned from history.
Question: What is a plot hole?
Answer: A plot hole is a plot point that happens in a fictional story, such as a movie, that contradicts the established logic of the story. For example, if a character is established as being extremely selfish, but in one scene he gives money to another character in need for no apparent reason, this would be a plot hole as this development would not make sense to a reasonable audience member.

Most plot holes can still be explained if someone tries hard enough, but if the story does not give enough clues for an audience member to easily understand what is going on, it is a plot hole.

Plot holes have different effects on different people. Some people are taken out of the story when they notice a plot hole. Others never notice it. Still others notice plot holes or learn of them afterwards, but do not mind the plot holes.
Question: Who are the greatest hockey players of all time?
Answer: The greatest hockey players of all time include Wayne Gretzky, Mario Lemieux, Bobby Orr, and Gordie Howe.
Question: Given this paragraph on Anton Chekhov, please tell me which playwrights he is most often grouped with?
Evidence: Anton Pavlovich Chekhov (Russian: Антон Павлович Чехов[note 1], IPA: [ɐnˈton ˈpavləvʲɪtɕ ˈtɕexəf]; 29 January 1860[note 2] – 15 July 1904[note 3]) was a Russian playwright and short-story writer who is considered to be one of the greatest writers of all time. His career as a playwright produced four classics, and his best short stories are held in high esteem by writers and critics. Along with Henrik Ibsen and August Strindberg, Chekhov is often referred to as one of the three seminal figures in the birth of early modernism in the theatre. Chekhov was a physician by profession. "Medicine is my lawful wife", he once said, "and literature is my mistress."
Answer: Chekhov is most often grouped with Henrik Ibsen and August Strindberg as one of the three seminal figures of early modernist theater.
Question: In the series A Song of Ice and Fire, who is the founder of House Stark?
Answer: Brandon Stark, also known as Brandon the Builder and Bran the Builder