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Question Answering by Reasoning Across Documents with Graph Convolutional Networks

arXiv 1808.09920 ↗First posted 29 Aug 2018cs.CL stat.MLcited by 56

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Abstract (arXiv)

Most research in reading comprehension has focused on answering questions based on individual documents or even single paragraphs. We introduce a neural model which integrates and reasons relying on information spread within documents and across multiple documents. We frame it as an inference problem on a graph. Mentions of entities are nodes of this graph while edges encode relations between different mentions (e.g., within- and cross-document co-reference). Graph convolutional networks (GCNs) are applied to these graphs and trained to perform multi-step reasoning. Our Entity-GCN method is scalable and compact, and it achieves state-of-the-art results on a multi-document question answering dataset, WikiHop (Welbl et al., 2018).

Key facts. Cited by 56 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Aug 2018.

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Citing papers per year: 2021: 24; 2022: 13; 2023: 11; 2024: 2; 2025: 6.

56 papers.

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  1. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)cited by 172
  2. 2021BertGCN: Transductive Text Classification by Combining GCN and BERTcited by 74
  3. 2021Multilingual Autoregressive Entity Linkingcited by 50
  4. 2021Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretablecited by 35
  5. 2021DAGN: Discourse-Aware Graph Network for Logical Reasoningcited by 28
  6. 2021GNN-LM: Language Modeling based on Global Contexts via GNNcited by 27
  7. 2023Causal Reasoning of Entities and Events in Procedural Textscited by 23
  8. 2021Highly Parallel Autoregressive Entity Linking with Discriminative Correctioncited by 21
  9. 2021Privacy-Preserving Graph Convolutional Networks for Text Classificationcited by 19
  10. 2021Rethinking Search: Making Domain Experts out of Dilettantescited by 18
  11. 2021GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Searchcited by 15
  12. 2021Complex Factoid Question Answering with a Free-Text Knowledge Graphcited by 14
38 more
  1. 2021Graph-free Multi-hop Reading Comprehension: A Select-to-Guide Strategycited by 13
  2. 2022Interpretable AMR-Based Question Decomposition for Multi-hop Question Answeringcited by 12
  3. 2023Generative Multimodal Entity Linkingcited by 12
  4. 2021Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialoguescited by 11
  5. 2022Reasoning over Hybrid Chain for Table-and-Text Open Domain QAcited by 10
  6. 2023Towards Personalized Review Summarization by Modeling Historical Reviews from Customer and Product Separatelycited by 9
  7. 2023Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networkscited by 9
  8. 2021Graph-Based Tri-Attention Network for Answer Ranking in CQAcited by 8
  9. 2021Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Modelcited by 8
  10. 2025GRADE: Generating multi-hop QA and fine-gRAined Difficulty matrix for RAG Evaluationcited by 8
  11. 2025Hierarchical Lexical Graph for Enhanced Multi-Hop Retrievalcited by 7
  12. 2022Improving Question Answering over Knowledge Graphs Using Graph Summarizationcited by 6
  13. 2022Beyond the Granularity: Multi-Perspective Dialogue Collaborative Selection for Dialogue State Trackingcited by 6
  14. 2021Predicting Patient Readmission Risk from Medical Text via Knowledge Graph Enhanced Multiview Graph Convolutioncited by 5
  15. 2024UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Modelscited by 5
  16. 2021Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answeringcited by 4
  17. 2021Reasoning Chain Based Adversarial Attack for Multi-hop Question Answeringcited by 4
  18. 2022IMCI: Integrate Multi-view Contextual Information for Fact Extraction and Verificationcited by 3
  19. 2022GNN-SL: Sequence Labeling Based on Nearest Examples via GNNcited by 3
  20. 2023LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehensioncited by 3
  21. 2025MHTS: Multi-Hop Tree Structure Framework for Generating Difficulty-Controllable QA Datasets for RAG Evaluationcited by 3
  22. 2025LiteLong: Resource-Efficient Long-Context Data Synthesis for LLMscited by 3
  23. 2021Model Agnostic Answer Reranking System for Adversarial Question Answeringcited by 2
  24. 2021Interactive Machine Comprehension with Dynamic Knowledge Graphscited by 2
  25. 2022Ask to Understand: Question Generation for Multi-hop Question Answeringcited by 2
  26. 2022Discourse-Aware Graph Networks for Textual Logical Reasoningcited by 2
  27. 2022Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmarkcited by 2
  28. 2023Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answeringcited by 2
  29. 2021Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehensioncited by 1
  30. 2021ClueReader: Heterogeneous Graph Attention Network for Multi-hop Machine Reading Comprehensioncited by 1
  31. 2022Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Studycited by 1
  32. 2022A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approachescited by 1
  33. 2022Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehensioncited by 1
  34. 2023Graph Attention with Hierarchies for Multi-hop Question Answeringcited by 1
  35. 2023Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Modelcited by 1
  36. 2023MemSum-DQA: Adapting An Efficient Long Document Extractive Summarizer for Document Question Answeringcited by 1
  37. 2025MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linkingcited by 1
  38. 2021A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documentscited by 0

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