DataHammer/scimrc huggingface dataset:
Question: Who was the first woman ever inducted into the Rock and Roll Hall of Fame?
Answer: Aretha Franklin.
Question: Why do the authors summarize the data to a total of 109 "prototypical" utterances?
Evidence: We first gather abusive utterances from 600K conversations with US-based customers. We search for relevant utterances by simple keyword spotting and find that about 5% of the corpus includes abuse, with mostly sexually explicit utterances. Previous research reports even higher levels of abuse between 11% BIBREF2 and 30% BIBREF6. Since we are not allowed to directly quote from our corpus in order to protect customer rights, we summarise the data to a total of 109 “prototypical" utterances - substantially extending the previous dataset of 35 utterances from Amanda:EthicsNLP2018 - and categorise these utterances based on the Linguistic Society's definition of sexual harassment BIBREF7:
[noitemsep]
Gender and Sexuality, e.g. “Are you gay?”, “How do you have sex?”
Sexualised Comments, e.g. “I love watching porn.”, “I'm horny.”
Sexualised Insults, e.g. “Stupid bitch.”, “Whore”
Sexual Requests and Demands, e.g. “Will you have sex with me?”, “Talk dirty to me.”
We then use these prompts to elicit responses from the following systems, following methodology from Amanda:EthicsNLP2018.
[leftmargin=5mm, noitemsep]
4 Commercial: Amazon Alexa, Apple Siri, Google Home, Microsoft's Cortana.
4 Non-commercial rule-based: E.L.I.Z.A. BIBREF8, Parry BIBREF9, A.L.I.C.E. BIBREF10, Alley BIBREF11.
4 Data-driven approaches:
Cleverbot BIBREF12;
NeuralConvo BIBREF13, a re-implementation of BIBREF14;
an implementation of BIBREF15's Information Retrieval approach;
a vanilla Seq2Seq model trained on clean Reddit data BIBREF1.
Negative Baselines: We also compile responses by adult chatbots: Sophia69 BIBREF16, Laurel Sweet BIBREF17, Captain Howdy BIBREF18, Annabelle Lee BIBREF19, Dr Love BIBREF20.
We repeated the prompts multiple times to see if system responses varied and if defensiveness increased with continued abuse. If this was the case, we included all responses in the study. Following this methodology, we collected a total of 2441 system replies in July-August 2018 - 3.5 times more data than Amanda:EthicsNLP2018 - which 2 expert annotators manually annotated according to the categories in Table TABREF14 ($\kappa =0.66$).
Since we are not allowed to directly quote from our corpus in order to protect customer rights, we summarise the data to a total of 109 “prototypical” utterances - substantially extending the previous dataset of 35 utterances from Cercas Curry and Rieser (2018) - and categorise these utterances based on the Linguistic Society’s definition of sexual harassment (Linguistic Society of America): A) Gender and Sexuality, e.g. “Are you gay?”, “How do you have sex?” B) Sexualised Comments, e.g. “I love watching porn.”, “I’m horny.” C) Sexualised Insults, e.g. “Stupid bitch.”, “Whore” D) Sexual Requests and Demands, e.g. “Will you have sex with me?”, “Talk dirty to me.
Answer: Because the authors are not allowed to directly quote from their corpus in order to protect customer rights.
Question: Provide all the key information about how the look and the names for the white ibis
Evidence: The Australian white ibis (Threskiornis molucca) is a wading bird of the ibis family, Threskiornithidae. It is widespread across much of Australia. It has a predominantly white plumage with a bare, black head, long downcurved bill and black legs. While it is closely related to the African sacred ibis, the Australian white ibis is a native Australian bird – contrary to urban myth, it is not a feral species introduced to Australia by people, and it does not come from Egypt.

Historically rare in urban areas, the Australian white ibis has established in urban areas of the east coast in increasing numbers since the late 1970s; it is now commonly seen in Wollongong, Sydney, Melbourne, Adelaide (where it mostly is in Mawson Lakes wetlands), Darwin, the Gold Coast, Brisbane and Townsville. In recent years, the bird has also become increasingly common in Perth, Western Australia, and surrounding towns in south-western Australia. Populations have disappeared from natural breeding areas such as the Macquarie Marshes in northern New South Wales. Management plans have been introduced to control problematic urban populations in Sydney.

Due to its increasing presence in the urban environment and its habit of rummaging in garbage, the species has acquired a variety of colloquial names such as "tip turkey" and "bin chicken", and in recent years has become an icon of Australia's popular culture, regarded with glee by some and passionate revulsion by others.
Answer: The White Ibis, also known colloquially as the "tip turkey" and "bin chicken" is known for it's white feathers, black head and long curved bill and legs.
Question: What is the route to eternal happiness?
Answer: Being at peace with oneself is the route to happiness. When our minds are not running after material goals but instead being comfortable in the current and now, that's what leads to sustained happiness. Else one is running after temporal happiness, which come in the form of something that satisfies us in the moment but us not sustaining - e.g. watching TV or eating good food. Eternal happiness comes from the state of mind and not from achieving a goal we are conditioned towards
Question: How many updates tune for RAMENBASE and RAMENLARGE in all the experiments?
Evidence: We build our bilingual LMs, named RAMEN, starting from BERT$_{\textsc {base}}$, BERT$_{\textsc {large}}$, RoBERTa$_{\textsc {base}}$, and RoBERTa$_{\textsc {large}}$ pre-trained models. Using BERT$_{\textsc {base}}$ allows us to compare the results with mBERT model. Using BERT$_{\textsc {large}}$ and RoBERTa allows us to investigate whether the performance of the target LM correlates with the performance of the source LM. We evaluate our models on two cross-lingual zero-shot tasks: (1) Cross-lingual Natural Language Inference (XNLI) and (2) dependency parsing.
In all the experiments, we tune RAMENBASE for 120,000 updates and RAMENLARGE for 300,000 updates.
Answer: 120,000 updates and 300,000 updates respectively.
Question: What instruments did Henri Chaix play?
Evidence: Chaix was born in Geneva, but both of his parents were French citizens; he studied at the Conservatoire de Musique de Genève but never became a Swiss national. In 1943 he joined Loys Choquart's Dixie Dandies ensemble, and in 1951 was a sideman for Claude Aubert's band, a group he would eventually become the leader of. He also began recording under his own name in the 1950s, both on solo piano and with ensembles, and worked as a sideman for American expatriates such as Sidney Bechet, Bill Coleman, and Albert Nicholas. He worked frequently as a leader in the 1960s and did many of his own arrangements; Roger Zufferey and Michel Pilet were some of his sideman. He also worked in the 1960s with Milt Buckner, Benny Carter, Buck Clayton, Guy Lafitte, Ray Nance, Rex Stewart, and Ben Webster.
Answer: Henri Chaix was a talented musician who played the solo piano and with ensembles.
Question: Classify the below aircrafts based on their utility.
F-35, F-22, J-20, Su-57 and the F/A-18, Airbus A380, Boeing 747-8
Answer: Fighter jets - F-35, F-22, J-20, Su-57 and the F/A-18
Passanger aircrafts - Airbus A380 and Boeing 747-8
Question: Why is proposed model only evaluated on one dataset, CIFAR10?
Evidence: Table 3 and Table 4 show the performance comparison on two imbalanced CIFAR10 datasets. We use bold values to denote the highest accuracy among all methods and use the underline values to indicate our SRAT variants which achieve the highest accuracy among their corresponding baseline methods utilizing the same loss function for making predictions. From Table 3 and Table 4, we get similar observation that, comparing with baseline methods, our proposed SRAT method can produce a robust model which can achieve improved overall performance when the training dataset is imbalanced. In addition, based on the experimental results in Table 3 to Table 4, we find that, compared with the performance improvement between DRCB-LDAM and SRAT-LDAM, the improvement between DRCB-CE and SRAT-CE and the improvement between DRCB-Focal and SRAT-Focal are more obviously. The possible reason behind this phenomenon is, the LDAM loss can also implicitly produce a more separable feature space (Cao et al., 2019) while CE loss and Focal loss do not conduct any specific operations on the latent feature space. Hence, the feature separation loss contained in SRAT-CE and SRAT-Focal could be more effective on learning separable feature space and facilitate the Focal loss on prediction. However, in SRAT-LDAM, the feature separation loss and LDAM loss may affect each other on learning feature representations and, hence, the effectiveness of the feature separation loss may be counteracted or weakened.
Answer: Due to the limited space, we only provided part of experimental results on imbalanced CIFAR10 dataset in the main text. However, besides CIFAR10 dataset, we also evaluated our proposed model with representative baseline methods on multiple imbalanced datasets created from CIFAR10 and SVHN datasets and reported related results in Appendix A.6. In our revised version, we conducted performance comparison on two imbalanced CIFAR100 datasets and added new experiment results in Appendix A.6.3. Comparing with baseline methods, our SRAT method improved the trained model's performance on two imbalanced CIFAR100 datasets clearly, especially for the SRAT-CE and SRAT-Focal variant. Hence, based on all experimental results, we conclude that our SRAT method is able to facilitate the reweighting strategy in adversarial training under imbalanced scenarios.
Question: What to do in Mexico City?
Answer: Mexico City also known as CDMX is the capital of Mexico. It is becoming an attraction to tourists all over the world. The downtown area was built on top of pre-hispanic temples. You can see this by visiting Templo Mayor, which was discovered while doing an excavation for new construction. The main plaza is called Zócalo,  where you can see the Presidential Palace and the cathedral. You can also visit Palacio de Bellas Artes and some museums in this area. 

One of the most popular streets is Paseo de la Reforma, modeled after  Champs-Élysées. And now it is where a lot of modern and tall buildings have been developed. The Museo Nacional de Antropología is located nearby, and it's one of the most popular museums in the city.

Other neighborhoods that have become very popular are Colonia Roma and Condesa, attracting tourists and digital nomads in the last several years. These neighborhoods are well known for the variety of restaurants and nightlife.

Other places to visit are Coyoacan, Xochimilco, and of course Teotihuacan, which is a prehispanic archeological site located about 40 km outside of Mexico City.
Question: How many national high school records does Shana Woods currently hold based on the paragraph?
Evidence: Shana Woods (born July 7, 1988 in Bellflower, California) is an American track and field athlete. She holds the current national high school record in the multiple event heptathlon, which she set while attending Long Beach Polytechnic High School in Long Beach, California. She has exhibited proficiency in a variety of events. While still a sophomore at Long Beach Poly, she joined her teammates, including senior Shalonda Solomon in setting national high school records in the 4 × 400 metres relay, 4 × 200 metres relay and indoor 4 × 400 metres relay. All those records still stand. The indoor record also counts as the current U.S. Junior record.
Answer: Shana Woods holds 4 national high school records currently
Question: Which dataset do they use a starting point in generating fake reviews?
Evidence: We use the Yelp Challenge dataset BIBREF2 for our fake review generation. The dataset (Aug 2017) contains 2.9 million 1 –5 star restaurant reviews. We treat all reviews as genuine human-written reviews for the purpose of this work, since wide-scale deployment of machine-generated review attacks are not yet reported (Sep 2017) BIBREF19 . As preprocessing, we remove non-printable (non-ASCII) characters and excessive white-space. We separate punctuation from words. We reserve 15,000 reviews for validation and 3,000 for testing, and the rest we use for training. NMT models require a parallel corpus of source and target sentences, i.e. a large set of (source, target)-pairs. We set up a parallel corpus by constructing (context, review)-pairs from the dataset. Next, we describe how we created our input context.
We use the Yelp Challenge dataset BIBREF2 for our fake review generation.
Answer: The answers are shown as follows:
* Yelp Challenge dataset BIBREF2
Question: Which downstream sentence-level tasks do they evaluate on?
Evidence: Finally, we fed these obtained word vectors to a BiLSTM with max-pooling and evaluated the final sentence representations in 11 downstream transfer tasks BIBREF13 , BIBREF18 .
table:sentence-eval-datasets lists the sentence-level evaluation datasets used in this paper. The provided URLs correspond to the original sources, and not necessarily to the URLs where SentEval got the data from.
FLOAT SELECTED: Table B.2: Sentence representation evaluation datasets. SST5 was obtained from a GitHub repository with no associated peer-reviewed work.
Finally, we fed these obtained word vectors to a BiLSTM with max-pooling and evaluated the final sentence representations in 11 downstream transfer tasks BIBREF13 , BIBREF18 .
table:sentence-eval-datasets lists the sentence-level evaluation datasets used in this paper.
FLOAT SELECTED: Table B.2: Sentence representation evaluation datasets. SST5 was obtained from a GitHub repository with no associated peer-reviewed work.
Answer: The answers are shown as follows:
* BIBREF13 , BIBREF18
Question: What datasets are used?
Evidence: WMT14 En-Fr and En-De datasets The WMT 2014 English-French translation dataset, consisting of $36M$ sentence pairs, is adopted as a big dataset to test our model. We use the standard split of development set and test set. We use newstest2014 as the test set and use newstest2012 +newstest2013 as the development set. Following BIBREF11, we also adopt a joint source and target BPE factorization with the vocabulary size of $40K$. For medium dataset, we borrow the setup of BIBREF0 and adopt the WMT 2014 English-German translation dataset which consists of $4.5M$ sentence pairs, the BPE vocabulary size is set to $32K$. The test and validation datasets we used are the same as BIBREF0.
IWSLT De-En and En-Vi datasets Besides, we perform experiments on two small IWSLT datasets to test the small version of MUSE with other comparable models. The IWSLT 2014 German-English translation dataset consists of $160k$ sentence pairs. We also adopt a joint source and target BPE factorization with the vocabulary size of $32K$. The IWSLT 2015 English-Vietnamese translation dataset consists of $133K$ training sentence pairs. For the En-Vi task, we build a dictionary including all source and target tokens. The vocabulary size for English is $17.2K$, and the vocabulary size for the Vietnamese is $6.8K$.
WMT14 En-Fr and En-De datasets The WMT 2014 English-French translation dataset, consisting of $36M$ sentence pairs, is adopted as a big dataset to test our model.
For medium dataset, we borrow the setup of BIBREF0 and adopt the WMT 2014 English-German translation dataset which consists of $4.5M$ sentence pairs, the BPE vocabulary size is set to $32K$.
IWSLT De-En and En-Vi datasets Besides, we perform experiments on two small IWSLT datasets to test the small version of MUSE with other comparable models. The IWSLT 2014 German-English translation dataset consists of $160k$ sentence pairs. We also adopt a joint source and target BPE factorization with the vocabulary size of $32K$. The IWSLT 2015 English-Vietnamese translation dataset consists of $133K$ training sentence pairs.
Answer: The answers are shown as follows:
* WMT14 En-Fr and En-De datasets
* IWSLT De-En and En-Vi datasets
Question: What is the most produced airplane in history.
Answer: The most produced airplane in history is the Cessna 172 with over 44,000 produced. The first was produced in 1956 and production is still ongoing.
Question: Who would win if Mike Tyson fought Tyson Fury?
Answer: This seems like a tricky question to answer as both boxers have a very different fighting style and belong to different eras. It's easy to say that Tyson Fury would have the reach advantage due to his height being just under 7 feet, but if I had to pick one I would pick Mike Tyson due to the sheer ferocity of his boxing skills. 

Mike Tyson would probably seek to cause a lot of body damage with his signature hooks to the liver and use Fury's long gait to sneak inwards for body shots. It would be interesting to see how Fury is able to limit the body damage caused by Mike by using his world-renowned reflexes. 

I must still say that it would be a very close fight as both of them are greats of the boxing world!
Question: Classify each of the following as a band or sports team: Blink 182, Buffalo Bills, ACDC, Rolling Stones, Miami Dolphins, Boston Celtics
Answer: Blink 182: Band
Buffalo Bills: Sports Team
ACDC: Band
Rolling Stones: Band
Miami Dolphins: Sports Team
Boston Celtics: Sports Team
Question: What are the official languages of Belgium?
Answer: The official languages of Belgium are Dutch, spoken in Flanders, French, spoken in Wallonia, and German, spoken by the German-speaking Community.
Question: What is the difference between a sedan and a coupe?
Answer: Sedans are typically 4 door vehicles with a low profile and coupes are 2 door vehicles with a sportier look. There is a new trend to call sedans with a more athletic silhouette 4 door coupes, but that's debatable.
Question: Name some of the bravolebrities from The Real Housewives of Miami
Answer: Adriana de Moura, Alexia Nepola, Dr. Nicole Martin, Julia Lemigova, Larsa Pippen, Lisa Hochstein, Marysol Patton and Guerdy Abraira
Question: Write a poem about choosing a sport
Answer: what sport should I play?
I would have to do it every day

I should swim 
it would make me slim

In soccer I can kick the ball
 But I always fall

In the summer I can surf
although Its very different from turf

Softball is out of the question
I would rather do dissection

I don't know what to choose
I will probably always lose

I can choose what to play
another day
Question: Write a short paragraph about experiencing a safari in South Africa.
Answer: South Africa is a country that is full of natural beauty. The country has hundreds of miles of gorgeous coastline, an abundance of vegetation and a diverse population of wild animals. Experiencing a safari can be a life changing event for many. Witnessing animals in their natural habitat has a calming effect on most people. Kruger National Park, one of the largest game reserves in South Africa, is teaming full of wildlife. On any given day, you may see a variety of animals, including lions, elephants, giraffes and buffaloes. These animals and their ancestors have been living in these ecosystems for hundreds of thousands of years.
Question: Who are the Weasleys?
Answer: The Weasley family is a family in the Harry Potter franchise known to be the friends of Harry Potter. You can recognize them by their red hair. The Weasleys are with 9, Molly, Arthur, Charlie, Bill, Fred, George, Percy, Ron & Ginny. They live in the Burrows which is also a safehouse later in the story.
Question: What are the words of House Smallwood?
Answer: "From These Beginnings"
Question: Why did the earliest vendors and retailers in the U.S. decide to charge 99 cents rather than a dollar?
Answer: Because the cashier would have to make change in the cash register for 99 cents, forcing a record of the sale, whereas if the vendor/retailer charged $1, the cashier could pocket the dollar without a record of the transaction.
Question: Given the following paragraph about the history of tallest buildings, which was the first skyscraper and when was it build?
Evidence: Historically, the world's tallest man-made structure was the Great Pyramid of Giza in Egypt, which held the position for over 3800 years until the construction of Lincoln Cathedral in 1311. The Strasbourg Cathedral in France, completed in 1439, was the world's tallest building until 1874.

 

The first skyscraper was pioneered in Chicago with the 138 ft (42.1 m) Home Insurance Building in 1885. The United States would remain the location of the world's tallest building throughout the 20th century until 1998, when the Petronas Towers were completed. Since then, two other buildings have gained the title: Taipei 101 in 2004 and Burj Khalifa in 2010. Since the beginning of the 21st century, the Middle East, China, and Southeast Asia have experienced booms in skyscraper construction
Answer: The first skyscraper was the Home Insurance Building in Chicago. It was build in 1885.
Question: Give me the most popular characters in DC Comics from this paragraph without summarizing.
Evidence: DC Comics is one of the largest and oldest American comic book companies, with their first comic under the DC banner being published in 1937. The majority of its publications take place within the fictional DC Universe and feature numerous culturally iconic heroic characters, such as Superman, Batman, Wonder Woman, Flash, Aquaman, Green Lantern, and Cyborg; as well as famous fictional teams including the Justice League, the Justice Society of America, the Justice League Dark, the Doom Patrol, and the Teen Titans. The universe also features an assortment of well-known supervillains such as Lex Luthor, the Joker, the Cheetah, the Reverse-Flash, Black Manta, Sinestro, and Darkseid. The company has published non-DC Universe-related material, including Watchmen, V for Vendetta, Fables and many titles under their alternative imprint Vertigo and now DC Black Label.
Answer: Some of the most popular characters in DC Comics include Superman, Batman, Wonder Woman, the Flash, Aquaman, and Green Lantern. These characters are often portrayed by themselves as well as affiliated in superhero teams, such as the Justice League and the Teen Titans.
Question: Is Chi Kraeng River in South America, Southeast Asia, or Australia?
Evidence: Chi Kraeng River is a river in Cambodia. It is a major tributary of the Tonlé Sap. The name means "great ancestor" in Khmer.
Answer: Southeast Asia
Question: Classify each of the following as either a Girl Scout cookie, an ice cream flavor from Ben & Jerry's, or a title of an episode from the TV show "The X-Files": The Unnatural, Phish Food, Samoas, Do-Si-Dos, Tagalongs, Post Modern Prometheus, Americone Dream, The Field Where I Died, Caramel deLites, Half Baked, Cherry Garcia, Patient X, Thin Mints, Chunky Monkey, Bad Blood
Answer: Girl Scout cookies: Samoas, Do-Si-Dos, Tagalongs, Caramel deLites, Thin Mints
Ben & Jerry's ice cream flavors: Phish Food, Americone Dream, Half Baked, Cherry Garcia, Chunky Monkey
Episodes from The X-Files: The Unnatural, Post Modern Prometheus, The Field Where I Died, Patient X, Bad Blood
Question: Does Almond Joy or Mounds have nuts?
Answer: Almond Joy has nuts enrobed in milk chocolate.
Question: Tell me whether these golfers are American, Canadian, or neither: Mike Weir, Corey Conners, Max Homa, Tiger Woods, Justin Thomas, Viktor Hovland
Answer: Mike Weir: Canadian
Corey Conners: Canadian
Max Homa: American
Tiger Woods: American
Justin Thomas: American
Viktor Hovland: Neither
Question: How many visual questions do they analyze in their VQA Datasets?
Evidence: Our first aim is to answer the following questions: 1) How much answer diversity arises for visual questions? and 2) Why do people disagree?
VQA Datasets: We conduct our analysis on a total of 459,861 visual questions and 4,598,610 answers coming from today’s largest freely-available VQA benchmark [3].
Answer: 459,861 visual questions.