【论文整理】EMNLP-IJCNLP 2019 Papers Poster & Demo Session Question Answering, Textual Inference

Poster & Demo Session

Question Answering, Textual Inference and Other Areas of Semantics

• Tree-structured Decoding for Solving Math Word Problems (#56)
• PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text (#86) [arXiv]
• Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning (#107) [arXiv]
• Finding Generalizable Evidence by Learning to Convince Q&A Models (#179) [arXiv]
• Ranking and Sampling in Open-domain Question Answering (#468)
• A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs (#618) [arXiv]
• Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss (#807)
• Multi-task Learning for Conversational Question Answering Over a Large-Scale Knowledge Base (#924) [arXiv]
• BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels (#1930) [arXiv]
• Language Models as Knowledge Bases? (#2085) [arXiv]
• NumNet: Machine Reading Comprehension with Numerical Reasoning (#2237) [arXiv]
• Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks (#2277) [arXiv]
• Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering (#2390) [arXiv]
• Adversarial Domain Adaptation for Machine Reading Comprehension (#2764) [arXiv]
• Incorporating External Knowledge into Machine Reading for Generative Question Answering (#2820) [arXiv]
• Answering questions by learning to rank - Learning to rank by answering questions (#2825) [arXiv]
• Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension (#2940) [arXiv]
• Revealing the Importance of Semantic Retrieval for Machine Reading at Scale (#2945) [arXiv]
• PubMedQA: A Dataset for Biomedical Research Question Answering (#2978) [arXiv]
• Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering (#3164)
• Answering Complex Open-domain Questions Through Iterative Query Generation (#3417) [arXiv]
• NL2pSQL: Generating Pseudo-SQL Queries from Under-specified Natural Language Questions (#3489)
• Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering (#4004) [arXiv]
• Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning (#147)
• Learning to Update Knowledge Graph by Reading News (#493)
• DIVINE: A Generative Adversarial Imitation Learning Framework for Knowledge Graph Reasoning (#709)
• Original Semantics-Oriented Attention and Deep Fusion Network for Sentence Matching (#829)
• Representation Learning with Ordered Relation Paths for Knowledge Graph Completion (#972) [arXiv]
• Collaborative Policy Learning for Open Knowledge Graph Reasoning (#1018) [arXiv]
• Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder (#1444) [arXiv]
• Asynchronous Deep Interaction Network for Natural Language Inference (#2257)
• Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange (#2830) [arXiv]
• Query-focused Scenario Construction (#3550) [arXiv]
• Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model (#3819)

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