Papers Multi-Hop Reading Comprehension
“Multi-Hop Reading Comprehension” 태그가 달린 논문 19편 · 필터 해제
Complex Reading Comprehension Through Question Decomposition
Multi-hop reading comprehension requires not only the ability to reason over raw text but also the ability to combine multiple evidence. We propose a novel learning approach that helps language models better understand d…
Language ModelingLanguage ModellingMulti-Hop Reading ComprehensionReading ComprehensionHow Well Do Multi-hop Reading Comprehension Models Understand Date Information?
Several multi-hop reading comprehension datasets have been proposed to resolve the issue of reasoning shortcuts by which questions can be answered without performing multi-hop reasoning. However, the ability of multi-hop…
Data AugmentationMulti-Hop Reading ComprehensionQuestion AnsweringReading ComprehensionDeep Inductive Logic Reasoning for Multi-Hop Reading Comprehension
Multi-hop reading comprehension requires an ability to reason across multiple documents. On the one hand, deep learning approaches only implicitly encode query-related information into distributed embeddings which fail t…
Deep LearningMulti-Hop Reading ComprehensionReading ComprehensionRelational ReasoningHow Well Do Multi-hop Reading Comprehension Models Understand Date Information?
Many previous works demonstrated that existing multi-hop reading comprehension datasets (e.g., HotpotQA) contain reasoning shortcuts, where the questions can be answered without performing multi-hop reasoning. Recently, …
Multi-Hop Reading ComprehensionReading ComprehensionSummarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension
How can we generate concise explanations for multi-hop Reading Comprehension (RC)? The current strategies of identifying supporting sentences can be seen as an extractive question-focused summarization of the input text.…
2kMulti-Hop Reading ComprehensionReading ComprehensionGraph-free Multi-hop Reading Comprehension: A Select-to-Guide Strategy
Multi-hop reading comprehension (MHRC) requires not only to predict the correct answer span in the given passage, but also to provide a chain of supporting evidences for reasoning interpretability. It is natural to model…
Multi-Hop Reading ComprehensionReading ComprehensionMulti-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network
Multi-hop reading comprehension across multiple documents attracts much attention recently. In this paper, we propose a novel approach to tackle this multi-hop reading comprehension problem. Inspired by human reasoning p…
Multi-Hop Reading ComprehensionReading ComprehensionGraph Sequential Network for Reasoning over Sequences
Recently Graph Neural Network (GNN) has been applied successfully to various NLP tasks that require reasoning, such as multi-hop machine reading comprehension. In this paper, we consider a novel case where reasoning is n…
Fact VerificationGraph Neural NetworkMachine Reading ComprehensionMulti-Hop Reading Comprehension+1Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents
Interpretable multi-hop reading comprehension (RC) over multiple documents is a challenging problem because it demands reasoning over multiple information sources and explaining the answer prediction by providing support…
Learning-To-RankMulti-Hop Reading ComprehensionMulti-Task LearningPrediction+2R4C: A Benchmark for Evaluating RC Systems to Get the Right Answer for the Right Reason
Recent studies have revealed that reading comprehension (RC) systems learn to exploit annotation artifacts and other biases in current datasets. This prevents the community from reliably measuring the progress of RC syst…
Multi-Hop Reading ComprehensionReading ComprehensionExplore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
Multi-hop reading comprehension requires the model to explore and connect relevant information from multiple sentences/documents in order to answer the question about the context. To achieve this, we propose an interpret…
Multi-Hop Reading ComprehensionReading ComprehensionSentenceMulti-hop Reading Comprehension through Question Decomposition and Rescoring
Multi-hop Reading Comprehension (RC) requires reasoning and aggregation across several paragraphs. We propose a system for multi-hop RC that decomposes a compositional question into simpler sub-questions that can be answ…
Decision MakingMulti-Hop Reading ComprehensionQuestion GenerationQuestion-Generation+1Compositional Questions Do Not Necessitate Multi-hop Reasoning
Multi-hop reading comprehension (RC) questions are challenging because they require reading and reasoning over multiple paragraphs. We argue that it can be difficult to construct large multi-hop RC datasets. For example,…
Information RetrievalMulti-Hop Reading ComprehensionReading ComprehensionRetrievalMulti-hop Reading Comprehension via Deep Reinforcement Learning based Document Traversal
Reading Comprehension has received significant attention in recent years as high quality Question Answering (QA) datasets have become available. Despite state-of-the-art methods achieving strong overall accuracy, Multi-H…
Decision MakingDeep Reinforcement LearningMulti-Hop Reading ComprehensionQuestion Answering+6Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
Multi-hop reading comprehension (RC) across documents poses new challenge over single-document RC because it requires reasoning over multiple documents to reach the final answer. In this paper, we propose a new model to …
Multi-Hop Reading ComprehensionReading ComprehensionCognitive Graph for Multi-Hop Reading Comprehension at Scale
We propose a new CogQA framework for multi-hop question answering in web-scale documents. Inspired by the dual process theory in cognitive science, the framework gradually builds a \textit{cognitive graph} in an iterativ…
Graph Neural NetworkMulti-hop Question AnsweringMulti-Hop Reading ComprehensionQuestion Answering+1Exploiting Explicit Paths for Multi-hop Reading Comprehension
We propose a novel, path-based reasoning approach for the multi-hop reading comprehension task where a system needs to combine facts from multiple passages to answer a question. Although inspired by multi-hop reasoning o…
Implicit RelationsKnowledge GraphsMulti-Hop Reading ComprehensionReading ComprehensionExploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks
Multi-hop reading comprehension focuses on one type of factoid question, where a system needs to properly integrate multiple pieces of evidence to correctly answer a question. Previous work approximates global evidence w…
Multi-Hop Reading ComprehensionQuestion AnsweringReading ComprehensionConstructing Datasets for Multi-hop Reading Comprehension Across Documents
Most Reading Comprehension methods limit themselves to queries which can be answered using a single sentence, paragraph, or document. Enabling models to combine disjoint pieces of textual evidence would extend the scope …
Multi-Hop Reading ComprehensionReading ComprehensionSentence