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id stringlengths 40 40	pid stringlengths 42 42	input stringlengths 8.37k 169k	output stringlengths 1 1.63k
fb5ce11bfd74e9d7c322444b006a27f2ff32a0cf	fb5ce11bfd74e9d7c322444b006a27f2ff32a0cf_0	Q: What is task success rate achieved? Text: Introduction A significant challenge when designing robots to operate in the real world lies in the generation of control policies that can adapt to changing environments. Programming such policies is a labor and time-consuming process which requires substantial technical e...	96-97.6% using the objects color or shape and 79% using shape alone
1e2ffa065b640e912d6ed299ff713a12195e12c4	1e2ffa065b640e912d6ed299ff713a12195e12c4_0	Q: What simulations are performed by the authors to validate their approach? Text: Introduction A significant challenge when designing robots to operate in the real world lies in the generation of control policies that can adapt to changing environments. Programming such policies is a labor and time-consuming process w...	a simulated binning task in which the robot is tasked to place a cube into a bowl as outlined by the verbal command
28b2a20779a78a34fb228333dc4b93fd572fda15	28b2a20779a78a34fb228333dc4b93fd572fda15_0	Q: Does proposed end-to-end approach learn in reinforcement or supervised learning manner? Text: Introduction A significant challenge when designing robots to operate in the real world lies in the generation of control policies that can adapt to changing environments. Programming such policies is a labor and time-consu...	supervised learning
b367b823c5db4543ac421d0057b02f62ea16bf9f	b367b823c5db4543ac421d0057b02f62ea16bf9f_0	Q: Are synonymous relation taken into account in the Japanese-Vietnamese task? Text: Introduction NMT systems have achieved better performance compared to statistical machine translation (SMT) systems in recent years not only on available data language pairs BIBREF1, BIBREF2, but also on low-resource language pairs BIB...	Yes
84737d871bde8058d8033e496179f7daec31c2d3	84737d871bde8058d8033e496179f7daec31c2d3_0	Q: Is the supervised morphological learner tested on Japanese? Text: Introduction NMT systems have achieved better performance compared to statistical machine translation (SMT) systems in recent years not only on available data language pairs BIBREF1, BIBREF2, but also on low-resource language pairs BIBREF3, BIBREF4. N...	No
7b3d207ed47ae58286029b62fd0c160a0145e73d	7b3d207ed47ae58286029b62fd0c160a0145e73d_0	Q: What is the dataset that is used in the paper? Text: Introduction The detection of anomalous trends in the financial domain has focused largely on fraud detection BIBREF0, risk modeling BIBREF1, and predictive analysis BIBREF2. The data used in the majority of such studies is of time-series, transactional, graph or ...	Unanswerable
d58c264068d8ca04bb98038b4894560b571bab3e	d58c264068d8ca04bb98038b4894560b571bab3e_0	Q: What is the performance of the models discussed in the paper? Text: Introduction The detection of anomalous trends in the financial domain has focused largely on fraud detection BIBREF0, risk modeling BIBREF1, and predictive analysis BIBREF2. The data used in the majority of such studies is of time-series, transacti...	Unanswerable
f80d89fb905b3e7e17af1fe179b6f441405ad79b	f80d89fb905b3e7e17af1fe179b6f441405ad79b_0	Q: Does the paper consider the use of perplexity in order to identify text anomalies? Text: Introduction The detection of anomalous trends in the financial domain has focused largely on fraud detection BIBREF0, risk modeling BIBREF1, and predictive analysis BIBREF2. The data used in the majority of such studies is of t...	No
5f6fac08c97c85d5f4f4d56d8b0691292696f8e6	5f6fac08c97c85d5f4f4d56d8b0691292696f8e6_0	Q: Does the paper report a baseline for the task? Text: Introduction The detection of anomalous trends in the financial domain has focused largely on fraud detection BIBREF0, risk modeling BIBREF1, and predictive analysis BIBREF2. The data used in the majority of such studies is of time-series, transactional, graph or ...	No
6adec34d86095643e6b89cda5c7cd94f64381acc	6adec34d86095643e6b89cda5c7cd94f64381acc_0	Q: What non-contextual properties do they refer to? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1, to si...	These features are derived directly from the word and capture the general tendency of a word being echoed in explanations.
62ba1fefc1eb826fe0cbac092d37a3e2098967e9	62ba1fefc1eb826fe0cbac092d37a3e2098967e9_0	Q: What is the baseline? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1, to simply highlighting features ...	random method , LSTM
93ac147765ee2573923f68aa47741d4bcbf88fa8	93ac147765ee2573923f68aa47741d4bcbf88fa8_0	Q: What are their proposed features? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1, to simply highlighti...	Non-contextual properties of a word, Word usage in an OP or PC (two groups), How a word connects an OP and PC., General OP/PC properties
14c0328e8ec6360a913b8ecb3e50cb27650ff768	14c0328e8ec6360a913b8ecb3e50cb27650ff768_0	Q: What are overall baseline results on new this new task? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1...	all of our models outperform the random baseline by a wide margin, he best F1 score in content words more than doubles that of the random baseline (0.286 vs. 0.116)
6073fa9050da76eeecd8aa3ccc7ecb16a238d83f	6073fa9050da76eeecd8aa3ccc7ecb16a238d83f_0	Q: What metrics are used in evaluation of this task? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1, to s...	F1 score
eacd7e540cc34cb45770fcba463f4bf968681d59	eacd7e540cc34cb45770fcba463f4bf968681d59_0	Q: Do authors provide any explanation for intriguing patterns of word being echoed? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the phil...	No
1124804c3702499b78cf0678bab5867e81284b6c	1124804c3702499b78cf0678bab5867e81284b6c_0	Q: What features are proposed? Text: Introduction Explanations are essential for understanding and learning BIBREF0. They can take many forms, ranging from everyday explanations for questions such as why one likes Star Wars, to sophisticated formalization in the philosophy of science BIBREF1, to simply highlighting fea...	Non-contextual properties of a word, Word usage in an OP or PC (two groups), How a word connects an OP and PC, General OP/PC properties
2b78052314cb730824836ea69bc968df7964b4e4	2b78052314cb730824836ea69bc968df7964b4e4_0	Q: Which datasets are used to train this model? Text: Introduction Asking relevant and intelligent questions has always been an integral part of human learning, as it can help assess the user's understanding of a piece of text (an article, an essay etc.). However, forming questions manually can be sometimes arduous. Au...	SQUAD
11d2f0d913d6e5f5695f8febe2b03c6c125b667c	11d2f0d913d6e5f5695f8febe2b03c6c125b667c_0	Q: How is performance of this system measured? Text: Introduction Increases in life expectancy in the last century have resulted in a large number of people living to old ages and will result in a double number of dementia cases by the middle of the century BIBREF0BIBREF1. The most common form of dementia is Alzheimer ...	using the BLEU score as a quantitative metric and human evaluation for quality
1c85a25ec9d0c4f6622539f48346e23ff666cd5f	1c85a25ec9d0c4f6622539f48346e23ff666cd5f_0	Q: How many questions per image on average are available in dataset? Text: Introduction Increases in life expectancy in the last century have resulted in a large number of people living to old ages and will result in a double number of dementia cases by the middle of the century BIBREF0BIBREF1. The most common form of ...	5 questions per image
37d829cd42db9ae3d56ab30953a7cf9eda050841	37d829cd42db9ae3d56ab30953a7cf9eda050841_0	Q: Is machine learning system underneath similar to image caption ML systems? Text: Introduction Increases in life expectancy in the last century have resulted in a large number of people living to old ages and will result in a double number of dementia cases by the middle of the century BIBREF0BIBREF1. The most common...	Yes
4b41f399b193d259fd6e24f3c6e95dc5cae926dd	4b41f399b193d259fd6e24f3c6e95dc5cae926dd_0	Q: How big dataset is used for training this system? Text: Introduction Increases in life expectancy in the last century have resulted in a large number of people living to old ages and will result in a double number of dementia cases by the middle of the century BIBREF0BIBREF1. The most common form of dementia is Alzh...	For the question generation model 15,000 images with 75,000 questions. For the chatbot model, around 460k utterances over 230k dialogues.
76377e5bb7d0a374b0aefc54697ac9cd89d2eba8	76377e5bb7d0a374b0aefc54697ac9cd89d2eba8_0	Q: How do they obtain word lattices from words? Text: Introduction Short text matching plays a critical role in many natural language processing tasks, such as question answering, information retrieval, and so on. However, matching text sequences for Chinese or similar languages often suffers from word segmentation, wh...	By considering words as vertices and generating directed edges between neighboring words within a sentence
85aa125b3a15bbb6f99f91656ca2763e8fbdb0ff	85aa125b3a15bbb6f99f91656ca2763e8fbdb0ff_0	Q: Which metrics do they use to evaluate matching? Text: Introduction Short text matching plays a critical role in many natural language processing tasks, such as question answering, information retrieval, and so on. However, matching text sequences for Chinese or similar languages often suffers from word segmentation,...	Precision@1, Mean Average Precision, Mean Reciprocal Rank
4b128f9e94d242a8e926bdcb240ece279d725729	4b128f9e94d242a8e926bdcb240ece279d725729_0	Q: Which dataset(s) do they evaluate on? Text: Introduction Short text matching plays a critical role in many natural language processing tasks, such as question answering, information retrieval, and so on. However, matching text sequences for Chinese or similar languages often suffers from word segmentation, where the...	DBQA, KBRE
f8f13576115992b0abb897ced185a4f9d35c5de9	f8f13576115992b0abb897ced185a4f9d35c5de9_0	Q: What languages do they look at? Text: Introduction The dynamics of language evolution is one of many interdisciplinary fields to which methods and insights from statistical physics have been successfully applied (see BIBREF0 for an overview, and BIBREF1 for a specific comprehensive review). In this work we revisit t...	Unanswerable
1fdcc650c65c11908f6bde67d5052087245f3dde	1fdcc650c65c11908f6bde67d5052087245f3dde_0	Q: Do they report results only on English data? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory visual...	Unanswerable
abad9beb7295d809d7e5e1407cbf673c9ffffd19	abad9beb7295d809d7e5e1407cbf673c9ffffd19_0	Q: Do they propose any further additions that could be made to improve generalisation to unseen speakers? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensiv...	Yes
265c9b733e4dfffb76acfbade4c0c9b14d3ccde1	265c9b733e4dfffb76acfbade4c0c9b14d3ccde1_0	Q: What are the characteristics of the dataset? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory visual...	synchronized acoustic and ultrasound data from 58 typically developing children, aged 5-12 years old (31 female, 27 male), data was aligned at the phone-level, 121fps with a 135 field of view, single ultrasound frame consists of 412 echo returns from each of the 63 scan lines (63x412 raw frames)
0f928732f226185c76ad5960402e9342c0619310	0f928732f226185c76ad5960402e9342c0619310_0	Q: What type of models are used for classification? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory vi...	feedforward neural networks (DNNs), convolutional neural networks (CNNs)
11c5b12e675cfd8d1113724f019d8476275bd700	11c5b12e675cfd8d1113724f019d8476275bd700_0	Q: Do they compare to previous work? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory visual biofeedbac...	No
d24acc567ebaec1efee52826b7eaadddc0a89e8b	d24acc567ebaec1efee52826b7eaadddc0a89e8b_0	Q: How many instances does their dataset have? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory visual ...	10700
2d62a75af409835e4c123a615b06235a352a67fe	2d62a75af409835e4c123a615b06235a352a67fe_0	Q: What model do they use to classify phonetic segments? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulat...	feedforward neural networks, convolutional neural networks
fffbd6cafef96eeeee2f9fa5d8ab2b325ec528e6	fffbd6cafef96eeeee2f9fa5d8ab2b325ec528e6_0	Q: How many speakers do they have in the dataset? Text: Introduction Ultrasound tongue imaging (UTI) uses standard medical ultrasound to visualize the tongue surface during speech production. It provides a non-invasive, clinically safe, and increasingly inexpensive method to visualize the vocal tract. Articulatory visu...	58
c034f38a570d40360c3551a6469486044585c63c	c034f38a570d40360c3551a6469486044585c63c_0	Q: How better is proposed method than baselines perpexity wise? Text: Introduction Recent development in neural language modeling has generated significant excitement in the open-domain dialog generation community. The success of sequence-to-sequence learning BIBREF0, BIBREF1 in the field of neural machine translation ...	Perplexity of proposed MEED model is 19.795 vs 19.913 of next best result on test set.
9cbea686732b5b85f77868ca47d2f93cf34516ed	9cbea686732b5b85f77868ca47d2f93cf34516ed_0	Q: How does the multi-turn dialog system learns? Text: Introduction Recent development in neural language modeling has generated significant excitement in the open-domain dialog generation community. The success of sequence-to-sequence learning BIBREF0, BIBREF1 in the field of neural machine translation has inspired re...	we extract the emotion information from the utterances in $\mathbf {X}$ by leveraging an external text analysis program, and use an RNN to encode it into an emotion context vector $\mathbf {e}$, which is combined with $\mathbf {c}_t$ to produce the distribution
6aee16c4f319a190c2a451c1c099b66162299a28	6aee16c4f319a190c2a451c1c099b66162299a28_0	Q: How is human evaluation performed? Text: Introduction Recent development in neural language modeling has generated significant excitement in the open-domain dialog generation community. The success of sequence-to-sequence learning BIBREF0, BIBREF1 in the field of neural machine translation has inspired researchers t...	(1) grammatical correctness, (2) contextual coherence, (3) emotional appropriateness
4d4b9ff2da51b9e0255e5fab0b41dfe49a0d9012	4d4b9ff2da51b9e0255e5fab0b41dfe49a0d9012_0	Q: Is some other metrics other then perplexity measured? Text: Introduction Recent development in neural language modeling has generated significant excitement in the open-domain dialog generation community. The success of sequence-to-sequence learning BIBREF0, BIBREF1 in the field of neural machine translation has ins...	No
180047e1ccfc7c98f093b8d1e1d0479a4cca99cc	180047e1ccfc7c98f093b8d1e1d0479a4cca99cc_0	Q: What two baseline models are used? Text: Introduction Recent development in neural language modeling has generated significant excitement in the open-domain dialog generation community. The success of sequence-to-sequence learning BIBREF0, BIBREF1 in the field of neural machine translation has inspired researchers t...	sequence-to-sequence model (denoted as S2S), HRAN
fb3687ea05d38b5e65fdbbbd1572eacd82f56c0b	fb3687ea05d38b5e65fdbbbd1572eacd82f56c0b_0	Q: Do they evaluate on relation extraction? Text: Introduction Building knowledge graphs (KG) over Web corpora is an important problem that has galvanized effort from multiple communities over two decades BIBREF0 , BIBREF1 . Automated knowledge graph construction from Web resources involves several different phases. Th...	No
b5d6357d3a9e3d5fdf9b344ae96cddd11a407875	b5d6357d3a9e3d5fdf9b344ae96cddd11a407875_0	Q: What is the baseline model for the agreement-based mode? Text: Introduction A learner language (interlanguage) is an idiolect developed by a learner of a second or foreign language which may preserve some features of his/her first language. Previously, encouraging results of automatically building the syntactic anal...	PCFGLA-based parser, viz. Berkeley parser BIBREF5, minimal span-based neural parser BIBREF6