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Dynamic Coattention Networks For Question Answering

arXiv 1611.01604 ↗First posted 5 Nov 2016cs.CL cs.AIcited by 49

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Abstract (arXiv)

Several deep learning models have been proposed for question answering. However, due to their single-pass nature, they have no way to recover from local maxima corresponding to incorrect answers. To address this problem, we introduce the Dynamic Coattention Network (DCN) for question answering. The DCN first fuses co-dependent representations of the question and the document in order to focus on relevant parts of both. Then a dynamic pointing decoder iterates over potential answer spans. This iterative procedure enables the model to recover from initial local maxima corresponding to incorrect answers. On the Stanford question answering dataset, a single DCN model improves the previous state of the art from 71.0% F1 to 75.9%, while a DCN ensemble obtains 80.4% F1.

Key facts. Cited by 49 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2016.

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Citing papers per year: 2021: 20; 2022: 12; 2023: 11; 2024: 4; 2025: 1; 2026: 1.

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  1. 2022OpenCQA: Open-ended Question Answering with Chartscited by 60
  2. 2021Natural Language Video Localization: A Revisit in Span-based Question Answering Frameworkcited by 55
  3. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  4. 2021Biomedical Question Answering: A Survey of Approaches and Challengescited by 46
  5. 2021Paradigm Shift in Natural Language Processingcited by 39
  6. 2021SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoisingcited by 27
  7. 2023Pushing the Limits of ChatGPT on NLP Taskscited by 27
  8. 2021Introspective Distillation for Robust Question Answeringcited by 25
  9. 2022Video Activity Localisation with Uncertainties in Temporal Boundarycited by 24
  10. 2021Spatio-Temporal Self-Attention Network for Video Saliency Predictioncited by 19
  11. 2023A Survey on Video Moment Localizationcited by 18
  12. 2021Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causalitycited by 17
37 more
  1. 2021Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matricescited by 17
  2. 2023When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendationcited by 17
  3. 2022From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answeringcited by 12
  4. 2022Multitask Pre-training of Modular Prompt for Chinese Few-Shot Learningcited by 11
  5. 2022Implicit Motion-Compensated Network for Unsupervised Video Object Segmentationcited by 10
  6. 2021Neural Attention Models in Deep Learning: Survey and Taxonomycited by 8
  7. 2022On the Usability of Transformers-based models for a French Question-Answering taskcited by 8
  8. 2023LAIT: Efficient Multi-Segment Encoding in Transformers with Layer-Adjustable Interactioncited by 7
  9. 2021Learning to Rehearse in Long Sequence Memorizationcited by 6
  10. 2021Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarizationcited by 6
  11. 2024Localizing Events in Videos with Multimodal Queriescited by 6
  12. 2021Coarse-grained decomposition and fine-grained interaction for multi-hop question answeringcited by 5
  13. 2021MINIMAL: Mining Models for Data Free Universal Adversarial Triggerscited by 4
  14. 2023Adapting Pre-trained Generative Models for Extractive Question Answeringcited by 4
  15. 2021A Coarse to Fine Question Answering System based on Reinforcement Learningcited by 2
  16. 2021CAR-Net: Unsupervised Co-Attention Guided Registration Network for Joint Registration and Structure Learningcited by 2
  17. 2022Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehensioncited by 2
  18. 2022Unified BERT for Few-shot Natural Language Understandingcited by 2
  19. 2023Attention-Based Methods For Audio Question Answeringcited by 2
  20. 2023Question Answering with Deep Neural Networks for Semi-Structured Heterogeneous Genealogical Knowledge Graphscited by 2
  21. 2024A Comprehensive Analysis of Static Word Embeddings for Turkishcited by 2
  22. 2021Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehensioncited by 1
  23. 2022Lite Unified Modeling for Discriminative Reading Comprehensioncited by 1
  24. 2023A Comprehensive Empirical Evaluation of Existing Word Embedding Approachescited by 1
  25. 2023Sentence Bag Graph Formulation for Biomedical Distant Supervision Relation Extractioncited by 1
  26. 2024Optimization Can Learn Johnson Lindenstrauss Embeddingscited by 1
  27. 2021Orthogonal Attention: A Cloze-Style Approach to Negation Scope Resolutioncited by 0
  28. 2021Sequential Attention Module for Natural Language Processingcited by 0
  29. 2021A Framework for Rationale Extraction for Deep QA modelscited by 0
  30. 2022An Automated Question-Answering Framework Based on Evolution Algorithmcited by 0
  31. 2022Exploring and Exploiting Multi-Granularity Representations for Machine Reading Comprehensioncited by 0
  32. 2022Feature-augmented Machine Reading Comprehension with Auxiliary Taskscited by 0
  33. 2023Around the GLOBE: Numerical Aggregation Question-Answering on Heterogeneous Genealogical Knowledge Graphs with Deep Neural Networkscited by 0
  34. 2023AST-MHSA : Code Summarization using Multi-Head Self-Attentioncited by 0
  35. 2024A Survey of Reasoning for Substitution Relationships: Definitions, Methods, and Directionscited by 0
  36. 2025Contrastive Learning Augmented Social Recommendationscited by 0
  37. 2026AutothinkRAG: Complexity-Aware Control of Retrieval-Augmented Reasoning for Image-Text Interactioncited by 0