DataHammer/scimrc huggingface dataset:
Question: In the modified IMP, when using clean labels for training, where is the randomness coming from? How is the expectation defined?
Evidence: In setting i, we use an untrained CNN as the dense model, and solve the DIP optimization (Ulyanov et al., 2018) θ ∗ = arg min θ E(fθ(z); ˜x), x∗ = fθ ∗ (z), (1) where E(; ) denotes the Mean Square Error (MSE), x˜ is the corrupted version of the image x ∈ R 3×H×W , fθ represents the dense model f with initial parameter θ and z is the random tensor that z ∈ R C×H×W . We choose the same hourglass architecture with skip connections as in (Ulyanov et al., 2018), to be the dense model by default. In setting ii, we follow Bora et al. (2017) to use a pre-trained GAN generator, to reconstruct the
unknown vector x∗ ∈ Rn, after observing m < n linear measurements of its entries with noise:y = Ax∗ + η, where A ∈ R
m×n is the measurement matrix and η ∈ R
m is the noise. Within the range of the pre-trained generator prior, GANs could reconstruct the vector x∗ with high perceptual quality. Following the recommendation of Jalal et al. (2020), we use the official pre-trained model PGAN (Karras et al., 2017).
Answer: We added more explanation to Section 3.1-”Neural Network as Priors: Two Settings” for a stronger logistic link between the two settings considered in this work, DIP and GAN CS, and a clearer presentation.
Question: how to survive on Mars
Answer: Surviving on Mars would be a challenging and dangerous endeavor. However, here are some steps that could increase your chances of survival:

Oxygen: Mars' atmosphere is mostly carbon dioxide, so you'll need to find a way to generate oxygen. One way is to use a process called electrolysis to extract oxygen from water.

Water: Water is essential for survival, so you'll need to find a source of water on Mars. This could be in the form of ice or underground reserves.

Food: Growing your own food on Mars would be difficult, but not impossible. You could use hydroponics or aeroponics to grow plants indoors, or find ways to grow crops outdoors.

Shelter: Mars' harsh environment would require a well-built shelter to protect you from the extreme cold, radiation, and dust storms. The shelter would need to be well insulated and sealed to prevent air leaks.

Energy: You'll need a reliable source of energy to power your shelter and equipment. Solar panels could be used to generate electricity, or nuclear reactors could be used for more efficient energy production.

Communications: Communication with Earth would be crucial for survival. You would need a reliable communication system to send and receive messages from Earth, as well as to coordinate with other astronauts on Mars.

Medical Supplies: Medical emergencies could arise on Mars, so having a well-stocked medical kit and the knowledge to treat basic medical issues would be important.

Mental Health: Living in isolation on Mars could take a toll on your mental health. Maintaining social connections with other astronauts, regular exercise, and engaging in activities to combat boredom would be important for mental health.

Surviving on Mars would require a great deal of preparation, resources, and expertise. It would also require a strong will to persevere through the challenges of living on an inhospitable planet.
Question: What is the average length of the claims?
Evidence: FLOAT SELECTED: Table 2: A summary of PERSPECTRUM statistics
We now provide a brief summary of [wave]390P[wave]415e[wave]440r[wave]465s[wave]485p[wave]525e[wave]535c[wave]595t[wave]610r[wave]635u[wave]660m. The dataset contains about INLINEFORM0 claims with a significant length diversity (Table TABREF19 ). Additionally, the dataset comes with INLINEFORM1 perspectives, most of which were generated through paraphrasing (step 2b). The perspectives which convey the same point with respect to a claim are grouped into clusters. On average, each cluster has a size of INLINEFORM2 which shows that, on average, many perspectives have equivalents. More granular details are available in Table TABREF19 .
FLOAT SELECTED: Table 2: A summary of PERSPECTRUM statistics
The dataset contains about INLINEFORM0 claims with a significant length diversity (Table TABREF19 ).
Answer: Average claim length is 8.9 tokens.
Question: Where did the team collect the dataset in their research?
Evidence: We collected a simplified dataset from Simple English Wikipedia that are freely available, which has been previously used for many text simplification methods BIBREF0 , BIBREF10 , BIBREF3 . The simple English Wikipedia is pretty easy to understand than normal English Wikipedia. We downloaded all articles from Simple English Wikipedia. For these articles, we removed stubs, navigation pages and any article that consisted of a single sentence. We then split them into sentences with the Stanford CorNLP BIBREF21 , and deleted these sentences whose number of words are smaller than 10 or large than 40. After removing repeated sentences, we chose 600K sentences as the simplified data with 11.6M words, and the size of vocabulary is 82K.
We collected a simplified dataset from Simple English Wikipedia that are freely available1, which has been previously used for many text simplification methods (Biran et al., 2011; Coster and Kauchak, 2011; Zhu et al., 2010).
Answer: From Simple English Wikipedia.
Question: What is hot pot?
Evidence: Hot pot or hotpot (simplified Chinese: 火锅; traditional Chinese: 火鍋; pinyin: huǒguō; lit. 'fire pot'), also known as soup-food or steamboat, is a dish whereby a heat source placed on the dining table keeps a pot of soup stock simmering, and a variety of Chinese foodstuffs and ingredients are served beside the pot for the diners to put into the hot stock.
Answer: Hot pot is a traditional Chinese dish that you put all kinds of food such as sliced beef/lamp, seafood, vegetables, meatballs into a boiled seasoned soup until they are fully cooked
Question: What approach is most commonly used for the input embedding layer?
Evidence: Various neural networks have been proposed for sentence pair modeling, all of which fall into two types of approaches. The sentence encoding approach encodes each sentence into a fixed-length vector and then computes sentence similarity directly. The model of this type has advantages in the simplicity of the network design and generalization to other NLP tasks. The sentence pair interaction approach takes word alignment and interactions between the sentence pair into account and often show better performance when trained on in-domain data. Here we outline the two types of neural networks under the same general framework:
•The Input Embedding Layer takes vector representations of words as input, where pretrained word embeddings are most commonly used, e.g. GloVe (Pennington et al., 2014) or Word2vec (Mikolov et al., 2013).
Answer: Pretrained word embeddings are most commonly used, e.g. GloVe (Pennington et al., 2014) or Word2vec (Mikolov et al., 2013).
Question: Which of the following are exercise equipment: bicycle, book, dumbbell, treadmill, spoon, television
Answer: A bicycle, dumbbell, and treadmill are all pieces of exercise equipment. Bicycles can be used to ride around outside or even indoors, they are a great way to improve your cardio health. Dumbbells are often used at a gym but can be used at home, they help to improve muscle mass through strength training. A treadmill is a great way to improve work on your cardio health by allowing you to run inside. A book is not a piece of exercise equipment as it does not require much physical effort to engage with. A spoon will help you in eating meals, but does little to improve your cardio health or strength. A television, or TV, can be watched while exercising, but cannot be exercised with.
Question: Name some of the bravolebrities from Married to Medicine
Answer: Anila Sajja, Dr. Contessa Metcalfe, Dr. Heavenly Kimes, Dr. Jacqueline Walters, Dr. Simone Whitmore, Toya Bush-Harris and Quad Webb
Question: In what language do multilingual people dream?
Answer: This answer really depends on whom you are speaking to. Some multilingual people dream in different languages and this depends on who they are interacting with within their dreams.  For example, if in the dream they are talking to their French mother they would reply in French, however when speaking to their English teacher they speak in English. Other multilingual people, in their dreams, speak in any language they know without a particular distinction. Some people just speak 1 language all the way through. Anyways, I’m sure there are even more variances that we are not aware of!
Question: What percentage of the world's population did the British Empire hold sway over?
Evidence: The British Empire was composed of the dominions, colonies, protectorates, mandates, and other territories ruled or administered by the United Kingdom and its predecessor states. It began with the overseas possessions and trading posts established by England between the late 16th and early 18th centuries. At its height it was the largest empire in history and, for over a century, was the foremost global power. By 1913, the British Empire held sway over 412 million people, 23 per cent of the world population at the time, and by 1920, it covered 35.5 million km2 (13.7 million sq mi), 24 per cent of the Earth's total land area. As a result, its constitutional, legal, linguistic, and cultural legacy is widespread. At the peak of its power, it was described as "the empire on which the sun never sets", as the Sun was always shining on at least one of its territories.
Answer: 23 per cent of the world population
Question: The following is an Abstract of a paper on Autism Spectrum Disorder. Based on this abstract  would it be a good idea to enroll a child with ASD into group sports? 
"Given the characteristics of people with Autism Spectrum Disorder, it is evident the difficulties they show in the development of social skills. The scarce participation of people with Autism Spectrum Disorder in group sports can be taken as a reference. The aim of this study was to analyse the impact of football on the development of social skills in children with Autism Spectrum Disorder. In order to measure the sporting impact, it was necessary to implement a football training programme with the intention of evaluating different social skills. Thirteen children participated in the programme, all of them with a diagnosis of Autism Spectrum Disorder and with a severity level of 1. The study was based on a pre-experimental, pre-test/post-test design. Non-parametric tests were used for the statistical analysis, applying the Wilcoxon test. Two specific tools on social skills were used for data collection. The results showed a generalised improvement in the dimensions linked to the social skills assessed. This highlights the possibility of considering group sport as an alternative to be taken into account to work on and enhance social skills in children with Autism Spectrum Disorder"
Answer: In this study, the authors assess 13 children with Autism Spectrum Disorder (ASD-Level 1)  on their social skills, before and after being enrolled in a football training program. The authors claim that the results showed an overall improvement in participant's social skills. 
This suggests that participating in group sports maybe considered as a method to improve children with ASD's social and communication skills.
Question: Total # of Documentary in Netflix since 2023
Evidence: Documentaries
Title	Premiere	Runtime	Language
Mumbai Mafia: Police vs The Underworld	January 6, 2023	1 h 27 min	English
The Hatchet Wielding Hitchhiker	January 10, 2023	1 h 25 min	English
Big Mäck: Gangsters and Gold	January 20, 2023	1 h 30 min	German
Pamela, a Love Story	January 31, 2023	1 h 52 min	English
Money Shot: The Pornhub Story	March 15, 2023	1 h 34 min	English
Caught Out: Crime. Corruption. Cricket.	March 17, 2023	1 h 17 min	English
Lewis Capaldi: How I'm Feeling Now	April 5, 2023	1 h 36 min	English
Answer: There are 8 Documentaries on netflix since 2023
Question: What is Taj Mahal?
Answer: The Taj Mahal 'Crown of the Palace' is an ivory-white marble mausoleum on the right bank of the river Yamuna in Agra, Uttar Pradesh, India. The Taj Mahal attracts more than 6 million visitors a year and in 2007, it was declared a winner of the New 7 Wonders of the World.
Question: Extract the symptoms of an asthma attack from this passage in a bulleted list.
Evidence: An acute asthma exacerbation is commonly referred to as an asthma attack. The classic symptoms are shortness of breath, wheezing, and chest tightness. The wheezing is most often when breathing out. While these are the primary symptoms of asthma, some people present primarily with coughing, and in severe cases, air motion may be significantly impaired such that no wheezing is heard. In children, chest pain is often present.
https://en.wikipedia.org/wiki/Asthma
Answer: -Shortness of breath
-Wheezing
-Chest tightness and/or pain
-Coughing
-Significantly impaired air motion
Question: What is the future for human?
Answer: This is a very wide open question. It could be two directions. One direction is that human would just disappear like the dinosaur.  One direction is that human would become a species like a god. For the first direction, it may be caused by many situations. e.g. Nuclear war from WW3, extreme climate change. For the other direction, reproduced energy is ready, all cancers can be cured, everything can be done with robot with AI, human life is unlimited.
Question: From this text, find out the pros and cons of dredging
Evidence: Dredging is the excavation of material from a water environment. Possible reasons for dredging include improving existing water features; reshaping land and water features to alter drainage, navigability, and commercial use; constructing dams, dikes, and other controls for streams and shorelines; and recovering valuable mineral deposits or marine life having commercial value. In all but a few situations the excavation is undertaken by a specialist floating plant, known as a dredger.

Dredging is carried out in many different locations and for many different purposes, but the main objectives are usually to recover material of value or use, or to create a greater depth of water. Dredges have been classified as suction or mechanical. Dredging systems can either be shore-based, brought to a location based on barges, or built into purpose built vessels.

Dredging has significant environmental impacts: it can disturb marine sediments, leading to both short- and long-term water pollution, destroy important seabed ecosystems, and can release legacy human-sourced toxins captured in the sediment. These environmental impacts can significantly hurt marine wildlife populations, contaminate sources of drinking water and interrupt economic activities such as fishing.
Answer: The benefits of dredging are:
1. improves existing water features for better drainage, navigability, and commercial use
2. important for constructing dams, dikes, and other controls for streams and shorelines
3. helps in recovering valuable mineral deposits or marine life having commercial value

The demerits of dredging are related to its severe environmental impact, for example:
1. it can disturb marine sediments, leading to both short- and long-term water pollution
2. it can destroy important seabed ecosystems
3. it can release legacy human-sourced toxins captured in the sediment
All the above impacts can significantly hurt marine wildlife populations, contaminate sources of drinking water and interrupt economic activities such as fishing.
Question: Is it possible for the authors to compare against strong baselines methods for knowledge graph completion such [1] and [2]? [1] Zhu, Zhaocheng, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang. "Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction." arXiv preprint arXiv:2106.06935 (2021).
[2] Zhang, Shuai, Yi Tay, Lina Yao, and Qi Liu. "Quaternion knowledge graph embeddings." arXiv preprint arXiv:1904.10281 (2019)
Evidence: Table A5: Comparable results with baselines, where there are 20% least frequent relations. Here we report the results in term of MR, MRR, Hit@K (K=1,3,10).****Table A6: Result comparisions with baselines on generalization setting by randomly removing 5% relations. Here we report the results in term of MR, MRR, Hit@K (K=1,3,10).****Table A7: Result comparisions with baselines on generalization setting by randomly removing 10% relations. Here we report the results in term of MR, MRR, Hit@K (K=1,3,10).****Table A8: Result comparisions with baselines on generalization setting by randomly removing 15% relations. Here we report the results in term of MR, MRR, Hit@K (K=1,3,10).****Table A9: Result comparisions with baselines on generalization setting by randomly removing 20% relations. Here we report the results in term of MR, MRR, Hit@K (K=1,3,10).
Answer: We include [1] (named QuatE in standard setting and QuatE in generalization settings) as a baseline method and update its results in Tables 6, A5, A6, A7, A8, A9. These results further verify the superiority of the proposed method in terms of MRR, Hit@1, Hit@3, Hit@10.
For [2], we are unable to find the source code and detailed hyper-parameter settings such as the dimensions of embedding in the paper. So, we do not presently include this work. However, we cite [2] and leave the comparison as future work.
Question: In the series A Song of Ice and Fire, who is the founder of House Crayne?
Answer: Rose of the Red Lake
Question: Tell whether these things smell nice or unpleasant: garbage, lemons, sweat, oceans, rain
Answer: garbage: smells unpleasant, lemons: smells nice, sweat: smells unpleasant, oceans: smell nice, rain: smells nice
Question: If time warping is applied, the number of samples per window is different right? So how do the authors deal with this? Is resampling applied maybe?
Evidence: Time warping random changes the speed of the timeline1 . The number of speed changes is 100 and the maximal ratio of max/min speed is 10. If necessary, over-sampling or sampling methods are adopted to ensure the length of the augmented instance is the same as the original one.****https://tsaug.readthedocs.io/****
Answer: As we have introduced in the initial version, we adopt the tool from https://tsaug.readthedocs.io.  With this function, we may generate augmented sequences with different lengths. We further apply over-sampling or sampling to make sure the length is the same as the original one. We have added more details here. Thanks for pointing it out.
Question: Give me a bulleted list of all of the Star Wars movies in order by release date.
Answer: 1. Episode IV: A New Hope (1977)
2. Episode V: The Empire Strikes Back (1980)
3. Episode VI: Return of the Jedi (1983)
4. Episode I: The Phantom Menace (1999)
5. Episode II: Attack of the Clones (2002)
6. Episode III: Revenge of the Sith (2005)
7. Episode VII: The Force Awakens (2015)
Question: Give me some ideas to manage my manager.
Answer: 1. Be honest
2. Communicate
3. Understand goals
4. Stay calm
5. Solve problems
6. Be positive
7. Share your knowledge
8. Be caring
9. Practice positive reinforcement
10. Be a strong performer
Question: Tell me whether these shows are animated or not: South Park, Rugrats, Curb Your Enthusiasm, House Hunters, Attack on Titan
Answer: South Park: Animated
Rugrats: Animated
Curb Your Enthusiasm: Not Animated
House Hunters: Not Animated
Attack on Titan: Animated
Question: It looks like learning to paraphrase questions, a neural scoring model and a answer selection model cannot be trained end-to-end. How are they trained?
Evidence: BIBREF11 revisit bilingual pivoting in the context of neural machine translation (NMT, BIBREF12 , BIBREF13 ) and present a paraphrasing model based on neural networks. At its core, NMT is trained end-to-end to maximize the conditional probability of a correct translation given a source sentence, using a bilingual corpus. Paraphrases can be obtained by translating an English string into a foreign language and then back-translating it into English. NMT-based pivoting models offer advantages over conventional methods such as the ability to learn continuous representations and to consider wider context while paraphrasing.
Paraphrases can be obtained by translating an English string into a foreign language and then back-translating it into English. 
Answer: using multiple pivot sentences
Question: Mention the Record labels Taylor was associated with.
Evidence: Taylor Alison Swift (born December 13, 1989) is an American singer-songwriter. Her genre-spanning discography, songwriting abilities and artistic reinventions have received critical praise and wide media coverage. Born in West Reading, Pennsylvania, Swift moved to Nashville at age 14 to become a country artist. She signed a songwriting deal with Sony/ATV Music Publishing in 2004 and a recording contract with Big Machine Records in 2005. Her 2006 self-titled debut album made her the first female country artist to write a U.S. platinum-certified album.
Swift's next albums, Fearless (2008) and Speak Now (2010), explored country pop. The former's "Love Story" and "You Belong with Me" were the first country songs to top the U.S. pop and all-genre airplay charts, respectively. She experimented with rock and electronic styles on Red (2012), which featured her first Billboard Hot 100 number-one song, "We Are Never Ever Getting Back Together", and eschewed her country image in her synth-pop album, 1989 (2014), supported by chart-topping songs "Shake It Off", "Blank Space", and "Bad Blood". Media scrutiny inspired the urban-flavored Reputation (2017) and its number-one single "Look What You Made Me Do".
Exiting Big Machine, Swift signed with Republic Records in 2018 and released her seventh studio album, Lover (2019), followed by the autobiographical documentary Miss Americana (2020). She ventured into indie folk and alternative rock in her 2020 albums Folklore and Evermore, whose singles "Cardigan" and "Willow" topped the Hot 100. Swift began re-recording her first six albums after a dispute over their masters, re-releasing two in 2021—Fearless (Taylor's Version) and Red (Taylor's Version). The latter's "All Too Well (10 Minute Version)" became the longest song to top the Hot 100. Her 2022 album Midnights and single "Anti-Hero" broke all-time streaming records. Swift has directed music videos and films, such as All Too Well: The Short Film (2021), and played supporting roles in others.
Having sold over 200 million records globally, Swift is one of the best-selling musicians in history. She is the most streamed woman on Spotify and the only act to have five albums open with over one million copies sold in the US. Among her accolades are 12 Grammy Awards, including three Album of the Year wins; an Emmy Award; 40 American Music Awards; 29 Billboard Music Awards; three IFPI Global Recording Artist of the Year awards; and 92 Guinness World Records. Swift has been featured in rankings such as Rolling Stone's 100 Greatest Songwriters of All Time, Billboard's Greatest of All Time Artists, the Time 100 and Forbes Celebrity 100. Honored with titles such as Artist of the Decade and Woman of the Decade, Swift is an advocate for artists' rights and women's empowerment. Her music is credited with influencing a generation of singers and songwriters.
Answer: Taylor Swift was associated with the following record labels:
1. Sony/ATV Music Publishing (2004) 
2. Big Machine Records (2005)
3. Republic Records (2018)
Question: When was Bobby Moore born and when did he die?
Evidence: Robert Frederick Chelsea Moore OBE (12 April 1941 – 24 February 1993) was an English professional footballer. He most notably played for West Ham United, captaining the club for more than ten years, and was the captain of the England national team that won the 1966 FIFA World Cup. He is widely regarded as one of the greatest defenders in the history of football, and was cited by Pelé as the greatest defender that he had ever played against.
Answer: Bobby Moore was born in 1941 and died in 1993.