DataHammer/scimrc huggingface dataset:
Question: Did they use other evaluation metrics?
Evidence: In this section, we present the experimental settings for pointer-generator network and language model. Our experiment, our pointer-generator model has 500-dimensional hidden states and word embeddings. We use 50k words as our vocabulary for source and target. We evaluate our pointer-generator performance using BLEU score. We take the best model as our generator and during the decoding stage, we generate 1-best and 3-best using beam search with a beam size of 5. For the input, we build a parallel monolingual corpus by translating the mixed language sequence using Google NMT to English ( INLINEFORM0 ) and Mandarin ( INLINEFORM1 ) sequences. Then, we concatenate the translated English and Mandarin sequences and assign code-switching sequences as the labels ( INLINEFORM2 ).
The baseline language model is trained using RNNLM BIBREF23 . Then, we train our 2-layer LSTM models with a hidden size of 500 and unrolled for 35 steps. The embedding size is equal to the LSTM hidden size for weight tying. We optimize our model using SGD with initial learning rates of INLINEFORM1 . If there is no improvement during the evaluation, we reduce the learning rate by a factor of 0.75. In each time step, we apply dropout to both embedding layer and recurrent network. The gradient is clipped to a maximum of 0.25. Perplexity measure is used in the evaluation.
We evaluate our pointer-generator performance using BLEU score.
The baseline language model is trained using RNNLM BIBREF23 .
Perplexity measure is used in the evaluation.


Answer: Yes.
Question: What are the three bands of Bay Miwok Native Americans associated with the area of Walnut Creek as per the passage. Display the results in a bulleted format.
Evidence: Walnut Creek is a city in Contra Costa County, California, United States, located in the East Bay region of the San Francisco Bay Area, about 16 miles (26 kilometers) east of the city of Oakland. With a total population of 70,127 per the 2020 census, Walnut Creek serves as a vibrant hub for its neighboring cities because of its location at the junction of the highways from Sacramento and San Jose (I-680) and San Francisco/Oakland (SR-24), and its accessibility by BART. Its active downtown neighborhood features hundred-year-old buildings and extensive high-end retail establishments. The city shares its borders with Clayton, Lafayette, Alamo, Pleasant Hill, and Concord.
Downtown Walnut CreekThere are three bands of Bay Miwok Native Americans associated with the area of Walnut Creek (the stream for which the city is named): the Saclan, whose territory extended through the hills east of present-day cities of Oakland, Rossmoor, Lafayette, Moraga and Walnut Creek; the Volvon (also spelled Bolbon, Wolwon or Zuicun), who were near Mt. Diablo; and the Tactan, located on the San Ramon Creek in present-day Danville and Walnut Creek.The city of Walnut Creek has developed within the earlier area of four extensive Mexican land grants. One of these land grants – measuring 18,000 acres (73 km2) – belonged to Juana Sanchez de Pacheco. The grant was called Rancho Arroyo de Las Nueces y Bolbones, named after the principal waterway, Arroyo de las Nueces (Walnut Creek in English), and for the local group of Volvon indigenous Americans (also known as Bolbones in Spanish). The Arroyo de las Nueces was named for the local species of walnut tree, the California Walnut. The two grandsons of Sanchez de Pacheco inherited the thousands of acres of land. One, Ygnacio Sibrian, built the first roofed home in the valley in about 1850.
Answer: Saclan
Volvon
Tactan
Question: How to benchmark the Doc2Vec models?
Evidence: Our framework combines text-embedding, geometric graph construction and multi-resolution community detection to identify, rather than impose, content-based clusters from free, unstructured text in an unsupervised manner.
Figure 1 shows a summary of our pipeline. First, we pre-process each document to transform text into consecutive word tokens, where words are in their most normalised forms, and some words are removed if they have no distinctive meaning when used out of context BIBREF5 , BIBREF6 . We then train a paragraph vector model using the Document to Vector (Doc2Vec) framework BIBREF7 on the whole set (13 million) of preprocessed text records, although training on smaller sets (1 million) also produces good results. This training step is only done once. This Doc2Vec model is subsequently used to infer high-dimensional vector descriptions for the text of each of the 3229 documents in our target analysis set. We then compute a matrix containing pairwise similarities between any pair of document vectors, as inferred with Doc2Vec. This matrix can be thought of as a full, weighted graph with documents as nodes and edges weighted by their similarity. We sparsify this graph to the union of a minimum spanning tree and a k-Nearest Neighbors (MST-kNN) graph BIBREF8 , a geometric construction that removes less important similarities but preserves global connectivity for the graph and, hence, for the dataset. The derived MST-kNN graph is analysed with Markov Stability BIBREF9 , BIBREF10 , BIBREF11 , BIBREF12 , a multi-resolution dynamics-based graph partitioning method that identifies relevant subgraphs (i.e., clusters of documents) at different levels of granularity. MS uses a diffusive process on the graph to reveal the multiscale organisation at different resolutions without the need for choosing a priori the number of clusters, scale or organisation. To analyse a posteriori the different partitions across levels of resolution, we use both visualisations and quantitative scores. The visualisations include word clouds to summarise the main content, graph layouts, as well as Sankey diagrams and contingency tables that capture the correspondences across levels of resolution and relationships to the hand-coded classifications. The partitions are also evaluated quantitatively to score: (i) their intrinsic topic coherence (using pairwise mutual information BIBREF13 , BIBREF14 ), and (ii) their similarity to the operator hand-coded categories (using normalised mutual information BIBREF15 ). We now expand on the steps of the computational framework.
We benchmarked the Doc2Vec models by scoring how well the document vectors represent the semantic topic structure: (i) calculating centroids for the 15 externally hand-coded categories;  (ii)selecting the 100 nearest reports for each centroid;  (iii) counting the number of incident reports (out of 1500) correctly assigned to their centroid.
Answer: By scoring how well the document vectors represent the semantic topic structure.
Question: Why the MT-RNN slightly outperforms the authors' model on SST?
Evidence: We apply the optimal hyperparameter settings and compare our model against the following state-of-the-art models:
NBOW Neural Bag-of-Words that simply sums up embedding vectors of all words.
PV Paragraph Vectors followed by logistic regression BIBREF21 .
MT-RNN Multi-Task learning with Recurrent Neural Networks by a shared-layer architecture BIBREF11 .
MT-CNN Multi-Task learning with Convolutional Neural Networks BIBREF8 where lookup tables are partially shared.
MT-DNN Multi-Task learning with Deep Neural Networks BIBREF9 that utilizes bag-of-word representations and a hidden shared layer.
GRNN Gated Recursive Neural Network for sentence modeling BIBREF1 .
As Table TABREF48 shows, our model obtains competitive or better performances on all tasks except for the QC dataset, as it contains poor correlations with other tasks. MT-RNN slightly outperforms our model on SST, as sentences from this dataset are much shorter than those from IMDB and MDSD, and another possible reason may be that our model are more complex and requires larger data for training. Our model proposes the designs of various interactions including coupling, local and global fusion, which can be further implemented by other state-of-the-art models and produce better performances.
MT-RNN slightly outperforms our model on SST, as sentences from this dataset are much shorter than those from IMDB and MDSD, and another possible reason may be that our model are more complex and requires larger data for training.
Answer: Because sentences from this dataset are much shorter than those from IMDB and MDSD, and another possible reason may be that authors' model are more complex and requires larger data for training.
Question: Are unknown words accounted for by their language model?
Evidence: Once we had the corpora ready, we used the KenLM Toolkit to train the N-gram language models on each corpus. We trained using both bigrams and trigrams on the tweet and news data. Our language models accounted for unknown words and were built both with and without considering sentence or tweet boundaries.
Our language models accounted for unknown words and were built both with and without considering sentence or tweet boundaries.
Answer: Yes.
Question: What are six different corporations with orange logos?
Answer: Six examples of retail corporations with orange logos may include Home Depot, Fanta, Penguin Books, Harley-Davidson, ING, and Nickelodeon.
Question: What is a dog better at than humans?
Answer: Dogs do many things better than humans.  They can detect problems in the body like low blood pressure, and the development of some diseases like cancer because of smells given off by the body.  They smell and and can hear better than people, they can run and swim faster, and show affection in an unbiased way for their entire life.
Question: Which is a species of fish? Skate or Scooter
Answer: Skate
Question: Please provide a brief history of coffee
Answer: The history of coffee dates back to centuries of old oral tradition in modern day Ethiopia. However, neither where coffee was first cultivated nor direct evidence of its consumption prior to the 15th century have been found. Sufi monasteries in Yemen employed coffee as an aid to concentration during prayers. Coffee later spread to the Levant and Persia in the early 16th century; it caused some controversy on whether it was halal in Ottoman and Mamluk society. Coffee arrived in Italy the second half of the 16th century through commercial Mediterranean trade routes, while Central and Eastern Europeans learnt of coffee from the Ottomans. By the mid 17th century, it had reached India and the East Indies. Coffee houses would establish themselves in Western Europe by the late 17th century, especially in England and Germany. One of the earliest cultivations of coffee in the New World was when Gabriel de Clieu brought coffee seedlings to Martinique in 1720. These beans later sprouted 18,680 coffee trees which enabled its spread to other Caribbean islands like Saint-Domingue and also to Mexico. By 1788, Saint-Domingue supplied half the world's coffee. By 1852, globally, Brazil became the largest producer of coffee and has held that status ever since. The period since 1950 saw the widening of the playing field due to the emergence of several other major producers, notably Colombia, Ivory Coast, Ethiopia, and Vietnam; the latter overtook Colombia and became the second-largest producer in 1999. Modern production techniques along with the mass productization of coffee has made it a household item today.
Question: Why are the Los Angeles Lakers the most famous and successful basketball franchise in the world?
Answer: The Los Angeles Lakers are the most famous and successful basketball franchise in the world because they have won the most championships of any any professional N.B.A = National Basketball Association team in the world in the modern era. The modern NBA era begins after the merger of two professional basketball leagues, the NBA and ABA (American Basketball Association) and the creation of the three point basket and twenty-four second clock. The Los Angeles Lakers won the Larry O'Brien championship trophy in 1980, 1982, 1985, 1987, 1988, 2000, 2001, 2002, 2009, 2010 and 2020.  The Lakers appeared in the championship game in 1949,1950,1952,1953,1954,1959,1962,1963,1965,1968,1969,1970,1972,1973,1980,1982, 1983,1984,1985, 1987,1988,1989,1991,2000,2001,2002,2004, 2008,2009,2010,2020. Famous Hall of Fame players include, Kobe Bryant, LeBron James, Magic Johnson, Jerry West, James Worthy, Kareem Abdul-Jabbar, Shaquille O'Neal, Elgin Baylor, Gail Goodrich, George Mikan, Pau Gasol and Wilt Chamberlain
Question: Identify which instrument is string or percussion: Bo, Gaohu
Answer: Gaohu is string, Bo is percussion.
Question: Which dataset do they use?
Evidence: In this paper, we study verifiable robustness, i.e., providing a certificate that for a given network and test input, no attack or perturbation under the specification can change predictions, using the example of text classification tasks, Stanford Sentiment Treebank (SST) BIBREF15 and AG News BIBREF16. The specification against which we verify is that a text classification model should preserve its prediction under character (or synonym) substitutions in a character (or word) based model. We propose modeling these input perturbations as a simplex and then using Interval Bound Propagation (IBP) BIBREF17, BIBREF18, BIBREF19 to compute worst case bounds on specification satisfaction, as illustrated in Figure FIGREF1. Since these bounds can be computed efficiently, we can furthermore derive an auxiliary objective for models to become verifiable. The resulting classifiers are efficiently verifiable and improve robustness on adversarial examples, while maintaining comparable performance in terms of nominal test accuracy.
In this paper, we study verifiable robustness, i.e., providing a certificate that for a given network and test input, no attack or perturbation under the specification can change predictions, using the example of text classification tasks, Stanford Sentiment Treebank (SST) BIBREF15 and AG News BIBREF16. 
Answer: The answers are shown as follows:
* Stanford Sentiment Treebank (SST) BIBREF15 and AG News BIBREF16
Question: Identify which instrument is string or percussion: Crystallophone, Kacapi
Answer: Kacapi is string, Crystallophone is percussion.
Question: Identify which car manufacturer is German or American: Jeep, Alpina
Answer: Alpina is German, Jeep is American
Question: What do they use for visualization to explore the language vector space?
Evidence: In this section, we present several experiments with the model described. For exploring the language vector space, we use hierarchical agglomerative clustering for visualization. For measuring performance, we use cross-entropy on held out-data. For this, we use a set of the 128 most commonly translated Bible verses, to ensure that the held-out set is as large and overlapping as possible among languages.
For exploring the language vector space, we use hierarchical agglomerative clustering for visualization.
Answer: Hierarchical agglomerative clustering.
Question: what are ISO compliant crypto currencies?
Answer: XRP and XLM are the most popular ISO 20022 compliant crypto currencies.
Question: What are all the name the country Singapore had been referred as in this text?
Evidence: The English name of "Singapore" is an anglicisation of the native Malay name for the country, Singapura (pronounced [siŋapura]), which was in turn derived from the Sanskrit word for "lion city" (Sanskrit: सिंहपुर; romanised: Siṃhapura; Brahmi: 𑀲𑀺𑀁𑀳𑀧𑀼𑀭; literally "lion city"; siṃha means "lion", pura means "city" or "fortress"). A Chinese account from the third century referred to a place as Pú Luó Zhōng (Chinese: 蒲 羅 中), which sounds like Malay for "island at the end of a peninsula." Early references to the name Temasek (or Tumasik) are found in the Nagarakretagama, a Javanese eulogy written in 1365, and a Vietnamese source from the same time period. The name possibly means "Sea Town", being derived from the Malay tasek, meaning "sea" or "lake". The Chinese traveller Wang Dayuan visited a place around 1330 named Danmaxi (Chinese: 淡馬錫; pinyin: Dànmǎxí; Wade–Giles: Tan Ma Hsi) or Tam ma siak, depending on pronunciation. Danmaxi may be a transcription of Temasek, alternatively, it may be a combination of the Malay Tanah meaning "land" and Chinese Xi meaning "tin," which was traded on the island.
Answer: The text refers to Singapore with the following names: Singapore, Singapura, Lion City, Pú Luó Zhōng, Island at the end of a peninsula, Temasek, Tumasik, Sea Town, Danmaxi, Tam ma siak.
Question: What are really considered the Seven Wonders of the World?
Answer: There is a lot of debate and even different classifications have come up to define what are the actual Seven Wonders of the World. There are some that are considered the Seven Ancient Wonders and there are some that are considered the New Seven Wonders, but there seems to be a definitive list of the Seven Wonders which is the following: 
The Great Wall of China
The Taj Mahal
The Colosseum
Chichen Itza
Machu Picchu
Christ the Redeemer
Petra
Question: Who are the most successful US Olympic swimmers?
Answer: Michael Phelps, Mark Spitz, Katie Ledecky, Missy Franklin
Question: Who is Scarlett Johansson
Evidence: Scarlett Ingrid Johansson (/dʒoʊˈhænsən/; born November 22, 1984) is an American actress. The world's highest-paid actress in 2018 and 2019, she has featured multiple times on the Forbes Celebrity 100 list. Time named her one of the 100 most influential people in the world in 2021. Her films have grossed over $14.3 billion worldwide, making Johansson the highest-grossing box office star of all time. She has received various accolades, including a Tony Award and a British Academy Film Award, in addition to nominations for two Academy Awards and five Golden Globe Awards.
Answer: Scarlett Ingrid Johansson, born November 22, 1984, is an American actress. The world's highest-paid actress in 2018 and 2019, she has featured multiple times on the Forbes Celebrity 100 list. Time named her one of the 100 most influential people in the world in 2021. Her films have grossed over $14.3 billion worldwide, making Johansson the highest-grossing box office star of all time. She has received various accolades, including a Tony Award and a British Academy Film Award, in addition to nominations for two Academy Awards and five Golden Globe Awards.
Question: What do the authors do about the 188 tokens?
Evidence: Visual dialog BIBREF0 is an interesting new task combining the research efforts from Computer Vision, Natural Language Processing and Information Retrieval. While BIBREF1 presents some tips and tricks for VQA 2.0 Challenge, we follow their guidelines for the Visual Dialog challenge 2018. Our models use attention similar to BIBREF2 to get object level image representations from Faster R-CNN model BIBREF3. We experiment with different encoder mechanisms to get representations of conversational history.
Out of 11319 tokens present in the dataset, we found 188 tokens missing from the pre-trained Glove embeddings, so we manually map these tokens to words conveying semantically similar meaning,  e.g. we map over ten variations of the word “yes”
Answer: Manually map these tokens to words conveying semantically similar meaning,  e.g. they map over ten variations of the word “yes”.
Question: Name someone who helped to stash national treasures during a war, so irreplaceable items would not fall into the hands of the enemy or become lost
Evidence: Evdokia Reshetnik was a Ukrainian zoologist and ecologist. She was a specialist in the mole-rats and ground squirrels of Ukraine, and was the first scientist to describe the sandy blind mole-rat of southern Ukraine in 1939. She played a key role in keeping the National Museum of Natural History at the National Academy of Sciences of Ukraine operable in the inter-war and immediate post-war periods, in spite of arrests by both the Gestapo and Soviet authorities. She was one of the people involved in hiding specimens of the museum to prevent them being taken by the Germans. She is known for arguing that ecology, species distribution, populations, utility, and variability, should be weighed before making determinations that labeled certain animals as pests and harmful to the environment. Though she was responsible for maintaining the historiography of scientific development in Ukraine, her own legacy was lost until the twenty-first century.
Answer: Evdokia Reshetnik, a Ukranian zoologist and ecologist, helped squirrel away natural history artifacts from a Ukranian museum of Natural History, keeping them from falling into the hands of the Germans. Ironically, the story of her courage was nearly lost, only resurfacing in the twenty-first century.
Question: Which model architecture do they use to build a model?
Evidence: The model is composed of an encoder (§SECREF5) and a decoder with the attention mechanism (§SECREF7) that are both implemented using recurrent neural networks (RNNs); the encoder converts source words into a sequence of vectors, and the decoder generates target language words one-by-one with the attention mechanism based on the conditional probability shown in the equation DISPLAY_FORM2 and DISPLAY_FORM3. The details are described below.
The model is composed of an encoder (§SECREF5) and a decoder with the attention mechanism (§SECREF7) that are both implemented using recurrent neural networks (RNNs); the encoder converts source words into a sequence of vectors, and the decoder generates target language words one-by-one with the attention mechanism based on the conditional probability shown in the equation DISPLAY_FORM2 and DISPLAY_FORM3.
Answer: The answers are shown as follows:
* model is composed of an encoder (§SECREF5) and a decoder with the attention mechanism (§SECREF7) that are both implemented using recurrent neural networks (RNNs)
Question: Why is summer in California so great?
Answer: California has a Mediterranean climate making summers ideal weather.  Very little rain, low humidity and mild temperatures allow Californians the ability to enjoy the outdoors all summer long and make it a huge travel destination this time of year!
Question: Who has the most #1 hits in country music?
Answer: George Strait. As of 2015, George Strait holds the record for the most country number-one singles with 44.
Question: Give me a list of five surf spots in Southern California
Answer: Rincon, Malibu, Salt Creek, Trestles, Blacks Beach
Question: Why does a US $20 bill have a vertical strip on it when held to light?
Answer: Paper money has counterfeit measures to ensure it is very difficult to duplicate/fake
Question: Classify the below characters based on whether they are created by Marvel comics or D.C. comics
 Spider-Man, Iron Man, Captain America, Thor, Doctor Strange, Superman, Batman, Wonder Woman, Flash, Aquaman
Answer: DC- Superman, Batman, Wonder Woman, Flash, Aquaman
Marvel- Spider-Man, Iron Man, Captain America, Thor, Doctor Strange