DataHammer/scimrc huggingface dataset:
Question: Please give me a bulleted list of the fundamentals of baseball
Evidence: Baseball is a bat-and-ball sport played between two teams of nine players each, taking turns batting and fielding. The game occurs over the course of several plays, with each play generally beginning when a player on the fielding team, called the pitcher, throws a ball that a player on the batting team, called the batter, tries to hit with a bat. The objective of the offensive team (batting team) is to hit the ball into the field of play, away from the other team's players, allowing its players to run the bases, having them advance counter-clockwise around four bases to score what are called "runs". The objective of the defensive team (referred to as the fielding team) is to prevent batters from becoming runners, and to prevent runners' advance around the bases. A run is scored when a runner legally advances around the bases in order and touches home plate (the place where the player started as a batter).

The principal objective of the batting team is to have a player reach first base safely; this generally occurs either when the batter hits the ball and reaches first base before an opponent retrieves the ball and touches the base, or when the pitcher persists in throwing the ball out of the batter's reach. Players on the batting team who reach first base without being called "out" can attempt to advance to subsequent bases as a runner, either immediately or during teammates' turns batting. The fielding team tries to prevent runs by getting batters or runners "out", which forces them out of the field of play. The pitcher can get the batter out by throwing three pitches which result in strikes, while fielders can get the batter out by catching a batted ball before it touches the ground, and can get a runner out by tagging them with the ball while the runner is not touching a base.

The opposing teams switch back and forth between batting and fielding; the batting team's turn to bat is over once the fielding team records three outs. One turn batting for each team constitutes an inning. A game is usually composed of nine innings, and the team with the greater number of runs at the end of the game wins. Most games end after the ninth inning, but if scores are tied at that point, extra innings are usually played. Baseball has no game clock, though some competitions feature pace-of-play regulations such as the pitch clock to shorten game time.
Answer: - Baseball is a bat-and-ball sport played between two teams of nine players each, taking turns batting and fielding.
- The object of the game in to score more runs than the opposing team.
- Runs are score only by the batting team during their at bats. While batting you are allowed 3 outs before you will have to switch with the fielding team. 
- A typical baseball game last 9 innings, but there can be extra innings added if there is a tie.
Question: What was used for word embeddings in the preprocessing step?
Evidence: In the preprocessing step, we used pre-trained GloVe vectors for word embeddings, and they would not be updated during training; We padded sentence number in each passage to 101, all word number in each sentence to 100. Word number of queries and choices were padded to 50. For all kernels of CNN, INLINEFORM0 , each of which has three different kernel width INLINEFORM1 ; each of them has same kernel number INLINEFORM2 . We utilized dropout in each CNN layer with dropout rate 0.8. We used Adam BIBREF8 optimizer to optimize our model with initial learning rate 0.001.
In the preprocessing step, we used pre-trained GloVe vectors for word embeddings, and they would not be updated during training; We padded sentence number in each passage to 101, all word number in each sentence to 100.
Answer: Pre-trained GloVe vectors were used for word embedding, and they would not be updated during training.
Question: Could you learn such embedding simply from the image annotations and without using visual information?
Evidence: Another approach for generating query and image representations is treating images as a black box. Without using pixel data, how well can we do? Given the statistics of our dataset (3B query, image pairs with 220M unique queries and 900M unique images), we know that different queries co-occur with the same images. Intuitively, if a query $q_1$ co-occurs with many of the same images as query $q_2$ , then $q_1$ and $q_2$ are likely to be semantically similar, regardless of the visual content of the shared images. Thus, we can use a method that uses only co-occurrence statistics to better understand how well we can capture relationships between queries. This method serves as a baseline to our initial approach leveraging image understanding.
Another approach for generating query and image representations is treating images as a black box.
Given the statistics of our dataset (3B query, image pairs with 220M unique queries and 900M unique images), we know that different queries co-occur with the same images. Intuitively, if a query $q_1$ co-occurs with many of the same images as query $q_2$ , then $q_1$ and $q_2$ are likely to be semantically similar, regardless of the visual content of the shared images. Thus, we can use a method that uses only co-occurrence statistics to better understand how well we can capture relationships between queries.
Answer: Yes.
Question: How did the author conduct the ablation experiment?
Evidence: In this section, we design an ablation study on the core modules of our model to explore their effectiveness. The dataset used in this experiment is SST-2. To conduct the experiment, we only replace the target module with other candidates while maintaining the other settings. To be specific, we focus on two modules, the leaf-LSTM and structure-aware tag embeddings (tag-level tree-LSTM). In the first case, the leaf-LSTM is replaced with a fully-connected layer with a $\tanh $ activation or Bi-LSTM. In the second case, we replace the structure-aware tag embeddings with naive tag embeddings or do not employ them at all.
The experimental results are depicted in Figure 3 . As the chart shows, our model outperforms all the other options we have considered. In detail, the left part of the chart shows that the leaf-LSTM is the most effective option compared to its competitors. Note that the sequential leaf-LSTM is somewhat superior or competitive than the bidirectional leaf-LSTM when both have a comparable number of parameters. We conjecture this may because a backward LSTM does not add additional useful knowledge when the structure of a sentence is already known. In conclusion, we use the uni-directional LSTM as a leaf module because of its simplicity and remarkable performance.
Meanwhile, the right part of the figure demonstrates that our newly introduced structure-aware embeddings have a real impact on improving the model performance. Interestingly, employing the naive tag embeddings made no difference in terms of the test accuracy, even though the absolute validation accuracy increased (not reported in the figure). This result supports our assumption that tag information should be considered in the structure.
In this section, we design an ablation study on the core modules of our model to explore their effectiveness. The dataset used in this experiment is SST-2. To conduct the experiment, we only replace the target module with other candidates while maintaining the other settings.
Answer: They design an ablation study on the core modules of their model to explore their effectiveness. The dataset used in this experiment is SST-2. To conduct the experiment, they only replace the target module with other candidates while maintaining the other settings.
Question: What are the two main differences between the author's work and previous work?
Evidence: Neural models of MT that go beyond the sentence-level are an active research area BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6, BIBREF7, BIBREF8, BIBREF10, BIBREF9, BIBREF11. Typically, the main MT system is modified to take additional context as its input. One limitation of these approaches is that they assume that parallel document-level training data is available.
Closest to our work are two-pass models for document-level NMT BIBREF24, BIBREF11, where a second, context-aware model takes the translation and hidden representations of the sentence-level first-pass model as its input. The second-pass model can in principle be trained on a subset of the parallel training data BIBREF11, somewhat relaxing the assumption that all training data is at the document level.
Our work is different from this previous work in two main respects. Firstly, we show that consistency can be improved with only monolingual document-level training data. Secondly, the DocRepair model is decoupled from the first-pass MT system, which improves its portability.
Our work is different from this previous work in two main respects. Firstly, we show that consistency can be improved with only monolingual document-level training data. Secondly, the DocRepair model is decoupled from the first-pass MT system, which improves its portability.
Answer: Firstly, they show that consistency can be improved with only monolingual document-level training data. Secondly, the DocRepair model is decoupled from the first-pass MT system, which improves its portability.
Question: Which part of the joke is more important in humor?
Evidence: In order to understand what may be happening in the model, we used the body and punchline only datasets to see what part of the joke was most important for humor. We found that all of the models, including humans, relied more on the punchline of the joke in their predictions (Table 2). Thus, it seems that although both parts of the joke are needed for it to be humorous, the punchline carries higher weight than the body. We hypothesize that this is due to the variations found in the different joke bodies: some take paragraphs to set up the joke, while others are less than a sentence.
In order to understand what may be happening in the model, we used the body and punchline only datasets to see what part of the joke was most important for humor. We found that all of the models, including humans, relied more on the punchline of the joke in their predictions (Table 2). Thus, it seems that although both parts of the joke are needed for it to be humorous, the punchline carries higher weight than the body. We hypothesize that this is due to the variations found in the different joke bodies: some take paragraphs to set up the joke, while others are less than a sentence.
Answer: The answers are shown as follows:
* the punchline of the joke
Question: What are the different ways to save money?
Answer: There are many ways, but to do a deep analysis, you must first understand where you spend the most money.  

Here are some opportunities to save money 
-eliminate recurring expenses such as subscriptions
-refinance expensive loans such as your mortgage
-reduce unnecessary or luxuries such as an outside coffee
-use your labor instead of hiring someone to do the work
-eat at home rather than eating out
Question: In which cities was the AFL Grand Final played during COVID-19 ?
Evidence: The COVID-19 pandemic affected the scheduling of the match in 2020 and 2021, as outbreaks of the virus in Melbourne during finals precluded unrestricted travel and mass gatherings in Victoria. In 2020, when most of the league's clubs had been relocated to Queensland for the majority of the season, the grand final was played at the Gabba in Brisbane, the first time it had been played outside Victoria. It was also played at night, the first time it was not played in the afternoon time slot. The following season, it was played at Optus Stadium in Perth in a twilight timeslot
Answer: The AFL Grand Final was played in Brisbane in 2020 and Perth in 2021 due to the COVID-19 pandemic. Usually the AFL Grand Final is played in Melbourne, Victoria.
Question: What is the 2nd amendment of the US constitution? Is it misunderstood?
Answer: The 2nd amendment of the US constitution relates to the right to bear arms.  The exact text, from the web, is "A well regulated Militia, being necessary to the security of a free State, the right of the people to keep and bear Arms, shall not be infringed."  This is a contentious law given that guns are a tool of violence.  And this amendment is touted by citizens of the US that want to buy and keep guns.  For me, the interesting part, often overlooked, is the preamble that a well regulated militia is necessary for the security of a free State.  This may have been relevant to all people in the 18th century.  Today, we already have that "militia".  All law officers and soldiers make up that militia.  The armed forces are well regulated and are tasked with protecting the nation.  We, the US, have the best military in the world.  So it is not necessary for any Tom, Dick, or Harry, without training or national perspective, to take up arms.  Especially when the process itself is getting more unregulated.  Gun control is necessary and not precluded by the 2nd amendment.  Safety of all citizens is indeed mandated by the constitution.
Question: What are the different type of coats of dogs?
Evidence: The coats of domestic dogs are of two varieties: "double" being familiar with dogs (as well as wolves) originating from colder climates, made up of a coarse guard hair and a soft down hair, or "single", with the topcoat only. Breeds may have an occasional "blaze", stripe, or "star" of white fur on their chest or underside. Premature graying can occur in dogs from as early as one year of age; this is associated with impulsive behaviors, anxiety behaviors, fear of noise, and fear of unfamiliar people or animals.
Answer: The coat of a dog varies depending on its breed. Typically a dog could have either a "double" coat or a "single" coat. "Double" coats are originated from breeds that live in colder climates. This type of coat consist of a coarse guard hair and a soft down hair. Dogs with "single" coat only has the topcoat.
Question: Eric Arthur Blaire was the real name of which author
Answer: George Orwell
Question: Write a brief history of the world as told from the perspective of a redwood.
Answer: The first thing I remember is darkness.  I had found myself nestled under a pile of leaves and broken branches, just starting to sprout from an old rotting stump.  It was pretty warm.  As I peeked into the crisp new air, I saw ferns, spiders, and buzzing flies surrounding me.  But the thing that caught my attention most of all was the bright blue sky.  I wondered what was out there and if I would ever get to see it.  I had just met this world and wanted to learn so much more.  But I was only 3 inches tall and couldn't see much of anything.  So I waited.

As I got taller, the days began to feel shorter.  My favorite part of the day was feeling the wind blow through my newly acquired canopy of needles.  It wasn't much to look at, but I was proud.  I'd often stare at the giant trees around me.  How I yearned to be one of the tall redwoods.  They were kings of the forest; nothing stood taller.  I wanted to see what they could see from way up there.  One day I'll be one of them.

Days turned to weeks, and weeks turned into years, and it all felt so rushed that I could hardly keep track of the changing world around me.  I had grown tall enough to see through a clearing in the upper canopy.  Beyond our patch of trees was a mountain of countless others.  Looking out into the endless distance, I began to feel small.  What a strange feeling.  One cloudy day, I saw a lightning bolt strike a hilltop.  Soon enough, bright orange flames erupted across the horizon.  What a peculiar sight.  What began as a curiosity soon became terror as the fire rushed closer to my area of the woods.  I could feel the warm wind on my face as the fire grew more prominent.  Mercifully, the dark clouds hanging overhead opened up to a torrential downpour.  Cold pelting raindrops replaced the warm breeze, night fell over the mountain, and the forest breathed a sigh of relief.  

I awoke to a strange sight when the sun returned the next day.  What was once hundreds of proud redwoods was now a deep black scar on the mountain.  That would be me one day.
Question: What's the percentage of the corpus includes abuse?
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 ($\kappa =0.66$).
We search for relevant utterances by simple keyword spotting and find that about 5% of the corpus includes abuse, with mostly sexually explicit utterances.
Answer: About 5%.
Question: What is alternative rock?
Evidence: Alternative rock (also known as alternative music, alt-rock, or simply alternative) is a category of rock music that emerged from the independent music underground of the 1970s and became widely popular in the 1990s. "Alternative" refers to the genre's distinction from mainstream or commercial rock or pop music. The term's original meaning was broader, referring to musicians influenced by the musical style or independent, DIY ethos of late-1970s punk rock.Traditionally, alternative rock varied in terms of its sound, social context, and regional roots. Throughout the 1980s, magazines and zines, college radio airplay, and word of mouth had increased the prominence and highlighted the diversity of alternative rock's distinct styles (and music scenes), such as noise pop, indie rock, grunge, and shoegaze. In September 1988, Billboard introduced "alternative" into their charting system to reflect the rise of the format across radio stations in the United States by stations like KROQ-FM in Los Angeles and WDRE-FM in New York, which were playing music from more underground, independent, and non-commercial rock artists.
Answer: Alternate rock is a form of rock music popularized in the early 1990s. It was formed to distinguish itself as an "Alternative" to commercial rock and pop music. Artists that fell into this category were more underground and had smaller independent record labels. Most artists were first heard on college radio stations or by word of mouth. In 1988, the genre was officially used by Billboard to accurately chart the rise of this new style being played by radio stations.
Question: In 1779 Abraham Darby built the worlds first what
Answer: Metal Bridge
Question: What are three capital cities in South America?
Answer: Three capital cities in South America are Montevideo, Quito, and Lima.
Question: From the following list, tell me whether these animals are real of fictitious: unicorn, alpaca, kangaroo rat, griffin, centaur, colossal squid
Answer: Unicorns, griffins and centaurs are fictitious animals while alpacas, kangaroo rats and colossal squids are real animals
Question: How is the Maasai dance called the Adumu commonly called by other peoples?
Evidence: Maasai music traditionally consists of rhythms provided by a chorus of vocalists singing harmonies while a song leader, or olaranyani, sings the melody. Unlike most other African tribes, Maasai widely use drone polyphony.

Women chant lullabies, humming songs, and songs praising their sons. Nambas, the call-and-response pattern, repetition of nonsensical phrases, monophonic melodies, repeated phrases following each verse being sung on a descending scale, and singers responding to their verses are characteristic of singing by females. When many Maasai women gather together, they sing and dance among themselves.

Eunoto, the coming-of-age ceremony of the warrior, can involve ten or more days of singing, dancing and ritual. The warriors of the Il-Oodokilani perform a kind of march-past as well as the Adumu, or aigus, sometimes referred to as "the jumping dance" by non-Maasai. (Both adumu and aigus are Maa verbs meaning "to jump" with adumu meaning "To jump up and down in a dance".)
Answer: The Adumu is known elsewhere as "the jumping dance" as part of it involves jumping high in the air.
Question: If each client was served by the same number of professionals, how many professionals (round to one decimal place) would each client be served by?
Evidence: RGP, formerly known as Resources Global Professionals, is the operating arm of Resources Connection, Inc. (NASDAQ:RGP). The company provides consulting services in the areas of finance & accounting; information management; governance, risk & compliance (GRC); human capital; legal & regulatory; corporate advisory & restructuring; strategic communications; and supply chain management. As of fiscal year ending May 28, 2016, the company employed 3,283 professionals in 68 offices in 20 countries around the world. The company reported serving over 1,700 clients. Company headquarters are located in Irvine, CA.
Answer: 3283 professionals and 1700 clients, so 3283/1700 = 1.9 professionals serving each client.
Question: What style of English did Shakespeare use?
Answer: The language in which Shakespeare wrote is referred to as Early Modern English, a linguistic period that lasted from approximately 1500 to 1750. The language spoken during this period is often referred to as Elizabethan English or Shakespearian English.