machine comprehension
Machine Comprehension with Discourse Relations
... Prior work has demonstrated the value of dis- course relations in related applications such as question answering (Jansen et al., 2014). Tradi- tionally, however, these approaches rely on out- puts from off-the-shelf ...
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Attention Based Convolutional Neural Network for Machine Comprehension
... This work takes the lead in presenting a CNN based neural network system for open-domain machine comprehension task. Our systems try to solve this task in a document projection way as well as a tex- tual ...
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Machine Comprehension using Rich Semantic Representations
... of machine comprehension. Ma- chine comprehension (Richardson et ...models machine comprehension as an extension to textual entailment, learning to out- put an answer that is best ...
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A Strong Lexical Matching Method for the Machine Comprehension Test
... Machine comprehension of text is the overarching goal of a great deal of re- search in natural language ...The Machine Comprehension Test (Richard- son et ...
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Learning Answer Entailing Structures for Machine Comprehension
... swers. Machine comprehension can benefit from such a pre-classification step, not only to constrain plausible answers, but also to allow the system to use different processing strategies for each cate- ...
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Structural Embedding of Syntactic Trees for Machine Comprehension
... Reading Comprehension. Reading comprehen- sion is a challenging task in NLP research. Since the release of the SQuAD data set, many works have been done to construct models on this mas- sive question answering ...
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Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension
... commonsense machine comprehension problem is far from set- tled by considering only explicit or a single kind of commonsense ...like comprehension and reasoning, there exist two main ...
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A Parallel Hierarchical Model for Machine Comprehension on Sparse Data
... ing. Comprehension tests pose questions based on short text passages to evaluate such ...vestigate machine comprehension on the challenging MCTest ...
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Learning and Knowledge Transfer with Memory Networks for Machine Comprehension
... We attempt to improve the training procedure for Memory Networks in order to increase the perfor- mance for machine comprehension by QA with small scale datasets. Firstly, we introduce an im- proved ...
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A Strong Lexical Matching Method for the Machine Comprehension Test
... Machine comprehension of text is the overarching goal of a great deal of re- search in natural language ...The Machine Comprehension Test (Richard- son et ...
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NewsQA: A Machine Comprehension Dataset
... In this paper, we present a challenging new largescale dataset for machine comprehension: NewsQA. It contains 119,633 natural language questions posed by crowdworkers on 12,744 news articles from CNN. In ...
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Machine Comprehension with Syntax, Frames, and Semantics
... We proposed several novel features for machine comprehension, including those based on frame semantics, dependency syntax, word embeddings, and coreference resolution. Empirical results demonstrate ...
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Measuring text readability with machine comprehension: a pilot study
... simplistic machine under- standing systems, described in § ...when comprehension is evaluated using cloze tests, all the systems make very little difference, if any, between texts of varying complexities, ...
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
... Towards the end goal of natural language under- standing, we introduce the Stanford Question An- swering Dataset, a large reading comprehension dataset on Wikipedia articles with crowdsourced question-answer ...
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Robust Machine Comprehension Models via Adversarial Training
... We explore the task of reading comprehension based question answering (Q&A), where we fo- cus on the Stanford Question Answering Dataset (SQuAD) (Rajpurkar et al., 2016), in which mod- els answer questions ...
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Machine Comprehension by Text to Text Neural Question Generation
... In this paper we reframe the standard MC task: rather than answering questions about a document, we teach machines to ask questions. Our work has several motivations. First, we believe that pos- ing appropriate questions ...
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Cross Lingual Machine Reading Comprehension
... on Machine Reading Comprehension (MRC) task, most of the previous works are solving English-based MRC problems, and there are few efforts on other languages mainly due to the lack of large-scale training ...
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NumNet: Machine Reading Comprehension with Numerical Reasoning
... Machine reading comprehension (MRC) aims to infer the answer to a question given the docu- ment. In recent years, researchers have proposed lots of MRC models (Chen et al., 2016; Dhingra et al., 2017; Cui ...
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Dataset for the First Evaluation on Chinese Machine Reading Comprehension
... as we have known that world knowledge is very impor- tant when we do reading comprehension in reality, which makes this dataset much artificial than real situation. Chen et al. (2016) also showed that the proposed ...
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A Span Extraction Dataset for Chinese Machine Reading Comprehension
... Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of ...reading comprehension datasets are mostly in ...Chinese machine read- ing comprehension to add ...
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