DataHammer/scimrc huggingface dataset:
Question: What is self advocacy?
Answer: Self advocacy is a process in which a person themselves or asks another individual, group, or community to discuss or publish the benefits of what that person has done with others that have external influence to benefit the original person seeking self-advocacy.  Self advocacy works well in corporate environments and is a behavior in start-up companies that does not make an impact on performance, ranking or promotion.
Question: Please provide 5 different variants of served coffee
Answer: 1. Cold Brew 
2. Americano 
3. Espresso 
4. Latte 
5. Cappuccino
Question: What are the words of House Waxley?
Answer: "Light in the Darkness"
Question: Which soft-selection approaches are evaluated?
Evidence: Previous attention-based methods can be categorized as soft-selection approaches since the attention weights scatter across the whole sentence and every word is taken into consideration with different weights. This usually results in attention distraction BIBREF7, i.e., attending on noisy or misleading words, or opinion words from other aspects. Take Figure FIGREF1 as an example, for the aspect place in the sentence “the food is usually good but it certainly is not a relaxing place to go”, we visualize the attention weights from the model ATAE-LSTM BIBREF2. As we can see, the words “good” and “but” are dominant in attention weights. However, “good” is used to describe the aspect food rather than place, “but” is not so related to place either. The true opinion snippet “certainly is not a relaxing place” receives low attention weights, leading to the wrong prediction towards the aspect place.
FLOAT SELECTED: Table 2: Experimental results (accuracy %) on all the datasets. Models in the first part are baseline methods. The results in the first part (except BERT-Original) are obtained from the prior work (Tay et al., 2018). Avg column presents macro-averaged results across all the datasets.
Previous attention-based methods can be categorized as soft-selection approaches since the attention weights scatter across the whole sentence and every word is taken into consideration with different weights. 
FLOAT SELECTED: Table 2: Experimental results (accuracy %) on all the datasets. Models in the first part are baseline methods. The results in the first part (except BERT-Original) are obtained from the prior work (Tay et al., 2018). Avg column presents macro-averaged results across all the datasets.
Answer: LSTM and BERT
Question: At what age can you get a driver's permit in the state of Washington?
Answer: 15
Question: Classify each of the follow weapons used by the US Military as a Fighter Jet, Rifle, Attack Helicopter, or Tank: M4 Carbine, F16 Falcon, M1 Abrams, F15 Eagle, AH64 Apache, M1903 Springfield, AH1 Cobra, M4 Sherman, F14 Tomcat, F86 Sabre
Answer: M4 Carbine - Rifle
F16 Falcon - Fighter Jet
M1 Abrams - Tank
F15 Eagle - Fighter Jet
AH64 Apache - Attack Helicopter
M1903 Springfield - Rifle
AH1 Cobra - Attack Helicopter
M4 Sherman - Tank
F14 Tomcat - Fighter Jet
F86 Sabre - Fighter Jet
Question: A client with whom you have been training for 10 weeks retakes a submaximal exercise test and finds that his heart rate is lower at each stage (workload) of the test. He is bothered by this because he thought his heart would be stronger and beat more times per minute. Brainstorm an easy-to-understand explanation to help him understand what is going on. How would you respond?
Answer: I would explain that, counterintuitively, the stronger your heart is, the less you can expect it to beat (lower heart rate). To explain it simply, his heart is more efficient; being able to pump the necessary amount of oxygen into his body without contracting as many times as before, i.e. the muscles of his heart are stronger. He can relax because his lower heart rate means he has better cardiovascular health now!
Question: Where is Florida?
Answer: Florida is a state in the southeast corner of the continental United States of America. It is a peninsula surrounded by the Atlantic Ocean to the east and the Gulf of Mexico to the west. To the north, it is surrounded by the states of Georgia and Alabama. Key West, Florida is the southern most point of the continental United States. Ka Lae, on the Big Island of Hawaii, is the southern most point out of all 50 United States.
Question: Give me some ideas for my son's birthday party.
Answer: There are several ways to plan a fun and engaging birthday party for your son.  To get started, it would be helpful to consider your son's interests.  From there, you can set that thing of interest as a theme and plan your party around it.  For example, let's say your son loves the car.  In that scenario, you could decorate the event space with car-related stuff and perhaps even order a cake shaped like a car!
Question: Are the entailment problems which depend on any non-trivial amount of world knowledge problematic from the point of view of training and testing systems for entailment?
Evidence: We find that entailment problems which depend on any non-trivial amount of world knowledge are problematic from the point of view of training and testing systems for entailment. Indeed, in the presence of a large number of arbitrary facts, the conclusion can come solely from such knowledge, completely ignoring the premise. At best, the premise is serving as priming the memory of the reader. We find this issue to happen in RTE in a significant number of cases, including some of those listed above. For example, in problem 454, it is common knowledge that a bomb was indeed dropped on Hiroshima — yet we may consider that the entailment does not hold as such.
We find that entailment problems which depend on any non-trivial amount of world knowledge are problematic from the point of view of training and testing systems for entailment.
Answer: Yes, they are.
Question: Based on this paragraph about dogs, what is a French Bulldog?
Evidence: The French Bulldog, French: Bouledogue Français, is a French breed of companion dog or toy dog. It appeared in Paris in the mid-nineteenth century, apparently the result of cross-breeding of Toy Bulldogs imported from England and local Parisian ratters.

It is commonly kept as a pet, and is among the most frequently registered dogs in a number of countries including Australia, the United Kingdom, and the United States.
Answer: The French Bulldog is a French breed of companion dog or toy dog. It is is among the most frequently registered dogs in a number of countries including Australia, the United Kingdom, and the United States.
Question: Identify which animal species is alive or extinct: Sarcosuchus, Plains Bison
Answer: Sarcosuchus is extinct, Plains Bison is alive.
Question: Why do we love movies so much?
Answer: Because movies allow us to experience all those things/situations which are hard to take place in real life, movies can satisfy our desires and imaginations. There are many stories in the film to which we can relate ourselves. That's why we are so attracted to and entertained by movies.
There are several genres of movies
Action, Comedy, Drama, Fantasy, Horror, Mystery, Romance, Thriller
Question: Give me three reasons why basketball is so popular.
Answer: Basketball is popular around the world because one, it is easy to learn the rules and everyone of all ages can learn the rules and play. Two, it's a team sport so it is fun to play with friends and is a way to make new friends. Three, it's exciting and has a fast pace of play  which makes it appeal to people around the world.
Question: Which of the following are bait for fishing and which are candy: live worms, gummy worms, lollipops, Hershey's kisses, crickets, and leeches.
Answer: The candies are gummy worms, lollipops, and Hershey’s kisses, and the fish bait is live worms, crickets, and leeches. It’s possible that some of the candies can be used as fish bait but non of items categorized as fish bait would be acceptable as candy.
Question: The experimental section is weak and contains comparison only to several simple tasks (introduced in Maron et al.). While these experimental results provide some knowledge about the model, and evaluation on real datasets (e.g., graph classification benchmarks ) would significantly strengthen the paper. If such an experiment is not possible for some reason  can the authors discuss this?
Evidence: We selected three benchmark datasets from the TU Dortmund data collection: MUTAG dataset, IMDB-BINARY, and IMDB-MULTI. These datasets are provided for classification, thus we treated the experiments as invariant tasks. Since the size of these datasets are small, we run the 10-folds cross-validation score for each dataset.
We selected three benchmark datasets from the TU Dortmund data collection(Kersting et al., 2016): MUTAG dataset, IMDB-BINARY, and IMDB-MULTI. These datasets are provided for classification, thus we treated the experiments as invariant tasks. Since the size of these datasets are small, we run the 10-folds cross-validation score for each dataset.
Answer: We added experiments on graph benchmark data. Only three graph benchmarks experiments were completed during the rebuttal period, but we are currently running classification experiments using point cloud dataset; ModelNet40. It was not in time for the rebuttal revision manuscript, but if our paper is accepted, we will include in the camera-ready manuscript the results of the ModelNet 40 and other baseline methods results of the graph benchmark dataset.
Question: Q: What is the risk of using a hand sanitizer that contains methanol (wood alcohol) or 1-propanol?
Answer: A: Methanol exposure can result in nausea, vomiting, headache, blurred vision, permanent blindness, seizures, coma, permanent damage to the nervous system or death. Although people using these products on their hands are at risk for methanol poisoning, young children who accidentally swallow these products and adolescents and adults who drink these products as an alcohol (ethanol) substitute are most at risk.

Swallowing or drinking a hand sanitizer with 1-propanol can result in decreased breathing and heart rate, among other serious symptoms, and can lead to death. Hand sanitizer with 1-propanol contamination can irritate your skin (or eyes, if exposed). Although it is rare, some people have reported allergic skin reactions. Learn more about methanol and 1-propanol toxicities.
Question: Which changes to the law are planned for the french pension reform?
Evidence: The pension reforms have been long-considered by Macron and his government. Reforming the pension system was a significant part of his platform for election in 2017, with initial protests and transport strikes in late 2019, prior to the COVID-19 pandemic which saw Macron delay the reforms further. Raising the retirement age was not part of these initial reforms, but another "plan to unify the complex French pension system" by "getting rid of the 42 special regimes for sectors ranging from rail and energy workers to lawyers was crucial to keep the system financially viable". On 26 October 2022, Macron announced in a televised interview that pension reform scheduled for 2023 intended to raise the retirement age to 65, specifically that the minimum retirement age to be able to receive a full pension would be "gradually increased" from 62 to 65 by 2031, by three months per year from September 2023 to September 2030. Furthermore, the number of years that contributions would need to be made to qualify for the full state pension would increase from 42 to 43 in 2027, meaning that some may have to work to 67 – the year at which a person is automatically able to receive a state pension from. In addition to this, France's 42 separate pension schemes would be "streamlined". Macron clarified he would be willing to "discuss the retirement age with unions and make potential amendments", and that not implementing the reforms would lead to a reduction in the size of pensions.

Details of the reforms were scheduled to be revealed on 15 December 2022, but were delayed further to 10 January 2023, as a courtesy to the Greens and Republicans who were in the midst of electing new leaders; postponing the reforms to allow Macron to consult with said new leaders before revealing said details.
Answer: President Macron plans to raise the retirement age from 62 to 65 by 2031. The plan is to gradually increase the age by 3 month per year from September 2023 to September 2030.
Question: What is the aim of Task 2 of the CoNLL–SIGMORPHON 2018?
Evidence: This paper describes our approach and results for Task 2 of the CoNLL–SIGMORPHON 2018 shared task on universal morphological reinflection BIBREF0 . The task is to generate an inflected word form given its lemma and the context in which it occurs.
Morphological (re)inflection from context is of particular relevance to the field of computational linguistics: it is compelling to estimate how well a machine-learned system can capture the morphosyntactic properties of a word given its context, and map those properties to the correct surface form for a given lemma.
There are two tracks of Task 2 of CoNLL–SIGMORPHON 2018: in Track 1 the context is given in terms of word forms, lemmas and morphosyntactic descriptions (MSD); in Track 2 only word forms are available. See Table TABREF1 for an example. Task 2 is additionally split in three settings based on data size: high, medium and low, with high-resource datasets consisting of up to 70K instances per language, and low-resource datasets consisting of only about 1K instances.
The baseline provided by the shared task organisers is a seq2seq model with attention (similar to the winning system for reinflection in CoNLL–SIGMORPHON 2016, BIBREF1 ), which receives information about context through an embedding of the two words immediately adjacent to the target form. We use this baseline implementation as a starting point and achieve the best overall accuracy of 49.87 on Task 2 by introducing three augmentations to the provided baseline system: (1) We use an LSTM to encode the entire available context; (2) We employ a multi-task learning approach with the auxiliary objective of MSD prediction; and (3) We train the auxiliary component in a multilingual fashion, over sets of two to three languages.
In analysing the performance of our system, we found that encoding the full context improves performance considerably for all languages: 11.15 percentage points on average, although it also highly increases the variance in results. Multi-task learning, paired with multilingual training and subsequent monolingual finetuning, scored highest for five out of seven languages, improving accuracy by another 9.86% on average.
The task is to generate an inflected word form given its lemma and the context in which it occurs.
Answer: The task is to generate an inflected word form given its lemma and the context in which it occurs.
Question: Which of these is edible or not edible:
1. Banana
2. Laptop
3. Marmite
4. Tape
5. Mushroom
6. Pizza
Answer: The following are edible:
1. Banana
2. Marmite
3. Pizza

The following are not edible:
1. Laptop
2. Tape

The following may or may not be edible: 
1. Mushroom
Question: A las vegas seven days trip itinerary including budget and activities for a group of 5 friends.
Answer: A las vegas 7-day trip from Bangalore to Las Vegas for a group of 5 people.
A trip begins with packing. Check the weather forecast for all your travel destinations and plan your clothes accordingly.
Your bag itinerary must have common medicines, and also, if you are allergic, be specific about packing what you need.
Always keep a pair of cloth in cabin baggage if check-in baggage has a delay - you can stay a day or two with the clothes packed in cabin baggage. 
Make sure to have some snacks in the cabin baggage 
Make sure to keep travel documents copy set in all luggage you carry. Make sure to have some local currency as well ready before you travel.
Make sure all hotels, Airport pickup and drop are booked, and you keep a copy of those documents.
Flight charges from Bangalore to LasVegas cost between 130k to 180k per person depending on the carrier and seat preference( Economy or first class)
Now that you have done pre checklist, now below are the things to do in Las Vegas
In Las Vegas - Visit the Bellagio fountain at night.
Check out High Roller Observation Wheel
Visit the Neon Museum
Walk at night in the las vegas strip
If you are interested in casinos, tons of casinos start from the Airport. In the las vegas strip, you can visit MGM Grand, The Venetian, etc., for Casinos. 
Visit the Shark Reef Aquarium at Mandalay Bay
Visit the Red Rock Canyon National Conservation Area
You can hire a rental car - The cost per day is approx. 70 to 100 USD per person if divided by all five people
Visit the Hoover Dam in a car
Next, you can plan for Zion National Park and prepare for hiking trails. 
Next move to Grand Canyon 
Stay in Page, Arizona 
From there, you can visit GC National Park's South rim and north rim
Don't miss Horseshoe Bend and Grand Canyon Lower and Upper Antelope Canyon tours
So these places can be covered in LasVegas for three days and Page, Arizona for three days
You can head back to LasVegas and Shopping for one day and catch the next flight back to your hometown
Expenses per person per day, 1000 USD to 1500 USD, depending on whether you are in a budget hotel. Except for Food. Food costs up to 50 to 100 USD per day.
Question: What is the analysis of mutations in cancer, in genomics?
Answer: In cancer, the genomes of affected cells are rearranged in complex or even unpredictable ways. Massive sequencing efforts are used to identify previously unknown point mutations in a variety of genes in cancer. Bioinformaticians continue to produce specialized automated systems to manage the sheer volume of sequence data produced, and they create new algorithms and software to compare the sequencing results to the growing collection of human genome sequences and germline polymorphisms. New physical detection technologies are employed, such as oligonucleotide microarrays to identify chromosomal gains and losses (called comparative genomic hybridization), and single-nucleotide polymorphism arrays to detect known point mutations. These detection methods simultaneously measure several hundred thousand sites throughout the genome, and when used in high-throughput to measure thousands of samples, generate terabytes of data per experiment. Again the massive amounts and new types of data generate new opportunities for bioinformaticians. The data is often found to contain considerable variability, or noise, and thus Hidden Markov model and change-point analysis methods are being developed to infer real copy number changes.

Two important principles can be used in the analysis of cancer genomes bioinformatically pertaining to the identification of mutations in the exome. First, cancer is a disease of accumulated somatic mutations in genes. Second cancer contains driver mutations which need to be distinguished from passengers.

With the breakthroughs that this next-generation sequencing technology is providing to the field of Bioinformatics, cancer genomics could drastically change. These new methods and software allow bioinformaticians to sequence many cancer genomes quickly and affordably. This could create a more flexible process for classifying types of cancer by analysis of cancer driven mutations in the genome. Furthermore, tracking of patients while the disease progresses may be possible in the future with the sequence of cancer samples.

Another type of data that requires novel informatics development is the analysis of lesions found to be recurrent among many tumors.
Question: Think up a short list of the best US Presidents
Answer: Abraham Lincoln, George Washington, FDR, Ronald Reagan, Dwight Eisenhower, Harry Truman, Thomas Jefferson
Question: What was the baseline model?
Evidence: To compare our results, we use the provided baseline, which is a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs. For pre-processing, in this case we do not preserve casing and delete English stopwords.
To compare our results, we use the provided baseline, which is a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs. 
Answer: The answers are shown as follows:
* a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs
Question: Given a reference text about Tiger Woods, tell me when they were born, what their real first name is, and what profession his niece has.
Evidence: Woods was born on December 30, 1975, in Cypress, California, to Earl and Kultida "Tida" Woods. He is their only child, though he has two half-brothers and a half-sister from his father's first marriage. Earl was a retired U.S. Army officer and Vietnam War veteran; he was born to African-American parents and was also said to have had European, Native American, and possibly Chinese ancestry. Kultida (née Punsawad) is originally from Thailand, where Earl met her when he was on a tour of duty there in 1968. She is of mixed Thai, Chinese, and Dutch ancestry. In 2002, ESPN claimed: "For the record, he is one-quarter Thai, one-quarter Chinese, one-quarter Caucasian, one-eighth African American and one-eighth Native American." Tiger has described his ethnic make-up as "Cablinasian" (a syllabic abbreviation he coined from Caucasian, Black, American Indian, and Asian).

Woods's first name, Eldrick, was chosen by his mother because it began with "E" (for Earl) and ended with "K" (for Kultida). His middle name Tont is a traditional Thai name. He was nicknamed Tiger in honor of his father's friend, South Vietnamese Colonel Vuong Dang Phong, who had also been known as Tiger.

Woods has a niece, Cheyenne Woods, who played for the Wake Forest University golf team and turned professional in 2012 when she made her pro debut in the LPGA Championship.[
Answer: Tiger Woods was borh on December 30, 1975. His real first name is "Eldrick". His niece, Cheyenne Woods, is a professional golfer.
Question: Whose back-translation approach did the team propose to use?
Evidence: We train an auxiliary system using NMT model from the simplified sentence to the ordinary sentence, which is first trained on the available parallel data. For leveraging simplified sentences to improve the quality of NMT model for text simplification, we propose to adapt the back-translation approach proposed by Sennrich et al. BIBREF11 to our scenario. More concretely, Given one sentence in simplified sentences, we use the simplified-ordinary system in translate mode with greedy decoding to translate it to the ordinary sentences, which is denoted as back-translation. This way, we obtain a synthetic parallel simplified-ordinary sentences. Both the synthetic sentences and the available parallel data are used as training data for the original NMT system.
For leveraging simplified sentences to improve the quality of NMT model for text simplification, we propose to adapt the back-translation approach proposed by Sennrich et al.(Sennrich et al., 2015) to our scenario.
Answer: Sennrich et al.