paper list

There are some papers about knowledge domain in ACL, EMNLP, WWW, AAAI, COLING, NAACL, CIKM, WSDM

ACL 会议

2021年

问答相关

  1. Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answering [paper]

  2. Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting [paper]

  3. Explanations for CommonsenseQA: New Dataset and Models [paper]

  4. Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction [paper]

  5. CoSQA: 20,000+ Web Queries for Code Search and Question Answering [paper]

  6. End-to-End Training of Neural Retrievers for Open-Domain Question Answering [paper]

  7. Few-Shot Question Answering by Pretraining Span Selection [paper]

  8. Robustifying Multi-hop QA through Pseudo-Evidentiality Training [paper]

  9. Generation-Augmented Retrieval for Open-Domain Question Answering [paper]

  10. Learning to Ask Conversational Questions by Optimizing Levenshtein Distance [paper]

  11. xMoCo: Cross Momentum Contrastive Learning for Open-Domain Question Answering [paper]

  12. TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance [paper]

  13. A Semantic-based Method for Unsupervised Commonsense Question Answering [paper]

  14. A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collections [paper]

  15. Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval [paper]

  16. Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering [paper]

  17. Engage the Public: Poll Question Generation for Social Media Posts [paper]

  18. Question Answering Over Temporal Knowledge Graphs [paper]

  19. Can Generative Pre-trained Language Models Serve As Knowledge Bases for Closed-book QA? [paper]

  20. UnitedQA: A Hybrid Approach for Open Domain Question Answering [paper]

  21. ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data [paper]

  22. Recursive Tree-Structured Self-Attention for Answer Sentence Selection [paper]

  23. GTM: A Generative Triple-wise Model for Conversational Question Generation [paper]

  24. Joint Models for Answer Verification in Question Answering Systems [paper]

  25. Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering [paper]

  26. Modeling Transitions of Focal Entities for Conversational Knowledge Base Question Answering [paper]

  27. A Gradually Soft Multi-Task and Data-Augmented Approach to Medical Question Understanding [paper]

  28. Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering [paper]

  29. Check It Again: Progressive Visual Question Answering via Visual Entailment [paper]

  30. A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering [paper]

  31. Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering [paper]

  32. Learning to Perturb Word Embeddings for Out-of-distribution QA [paper]

问题生成

papers

  1. Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting[paper]

  2. Engage the Public: Poll Question Generation for Social Media Posts[paper]

  3. GTM: A Generative Triple-wise Model for Conversational Question Generation[paper]

  4. Controllable Open-ended Question Generation with A New Question Type Ontology[paper]

  5. Question Generation for Adaptive Education[paper]

Findings

  1. Learning to Generate Questions by Learning to Recover Answer-containing Sentences[paper]

  2. Multi-Lingual Question Generation with Language Agnostic Language Model[paper]

  3. Latent Reasoning for Low-Resource Question Generation[papaer]

emnlp会议

2021年

问题生成

papers

  1. Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing[paper]

  2. Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering[paper]

  3. Improving Unsupervised Question Answering via Summarization-Informed Question Generation[paper]

  4. Asking It All: Generating Contextualized Questions for any Semantic Role[paper]

  5. Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval[paper]

  6. Open-domain clarification question generation without question examples[paper]

Findings

  1. Simple or Complex? Complexity-controllable Question Generation with Soft Templates and Deep Mixture of Experts Model[paper]