mlsanityData to 7 Oct 2026

Coreferential Reasoning Learning for Language Representation

arXiv 2004.06870 ↗First posted 15 Apr 2020cs.CLcited by 80

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Abstract (arXiv)

Language representation models such as BERT could effectively capture contextual semantic information from plain text, and have been proved to achieve promising results in lots of downstream NLP tasks with appropriate fine-tuning. However, most existing language representation models cannot explicitly handle coreference, which is essential to the coherent understanding of the whole discourse. To address this issue, we present CorefBERT, a novel language representation model that can capture the coreferential relations in context. The experimental results show that, compared with existing baseline models, CorefBERT can achieve significant improvements consistently on various downstream NLP tasks that require coreferential reasoning, while maintaining comparable performance to previous models on other common NLP tasks. The source code and experiment details of this paper can be obtained from https://github.com/thunlp/CorefBERT.

Key facts. Cited by 80 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2020.

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Citing papers per year: 2021: 22; 2022: 26; 2023: 16; 2024: 12; 2025: 4.

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  1. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  2. 2021Document-level Relation Extraction as Semantic Segmentationcited by 80
  3. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  4. 2021Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extractioncited by 68
  5. 2021Few-Shot Question Answering by Pretraining Span Selectioncited by 62
  6. 2021DialFact: A Benchmark for Fact-Checking in Dialoguecited by 62
  7. 2021ProoFVer: Natural Logic Theorem Proving for Fact Verificationcited by 52
  8. 2024CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Modelscited by 50
  9. 2021Learning to Retrieve Passages without Supervisioncited by 46
  10. 2022Synthetic Disinformation Attacks on Automated Fact Verification Systemscited by 44
  11. 2022Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillationcited by 39
  12. 2021An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learningcited by 31
38 more
  1. 2021SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extractioncited by 30
  2. 2021Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusioncited by 28
  3. 2021Graph Based Network with Contextualized Representations of Turns in Dialoguecited by 26
  4. 2021SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extractioncited by 23
  5. 2023LIQUID: A Framework for List Question Answering Dataset Generationcited by 19
  6. 2022DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Populationcited by 17
  7. 2022Prompt Tuning for Discriminative Pre-trained Language Modelscited by 17
  8. 2021QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositionscited by 16
  9. 2022Document-Level Relation Extraction with Sentences Importance Estimation and Focusingcited by 16
  10. 2021Learning Logic Rules for Document-level Relation Extractioncited by 15
  11. 2021A Multi-Level Attention Model for Evidence-Based Fact Checkingcited by 13
  12. 2022Can Pre-trained Language Models Interpret Similes as Smart as Human?cited by 13
  13. 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systemscited by 11
  14. 2023BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verificationcited by 11
  15. 2025GLiREL -- Generalist Model for Zero-Shot Relation Extractioncited by 11
  16. 2023Document-level Relation Extraction with Cross-sentence Reasoning Graphcited by 9
  17. 2022Generalized Quantifiers as a Source of Error in Multilingual NLU Benchmarkscited by 8
  18. 2022None Class Ranking Loss for Document-Level Relation Extractioncited by 8
  19. 2022Commonsense and Named Entity Aware Knowledge Grounded Dialogue Generationcited by 8
  20. 2024[Lions: 1] and [Tigers: 2] and [Bears: 3], Oh My! Literary Coreference Annotation with LLMscited by 8
  21. 2024LLM with Relation Classifier for Document-Level Relation Extractioncited by 8
  22. 2022Towards Better Document-level Relation Extraction via Iterative Inferencecited by 7
  23. 2021REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-trainingcited by 6
  24. 2022Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extractioncited by 6
  25. 2021CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Modelscited by 5
  26. 2021Coreference Resolution for the Biomedical Domain: A Surveycited by 5
  27. 2022CorefDRE: Document-level Relation Extraction with coreference resolutioncited by 5
  28. 2023Unsupervised Pretraining for Fact Verification by Language Model Distillationcited by 5
  29. 2024FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation Extractioncited by 5
  30. 2024Building A Coding Assistant via the Retrieval-Augmented Language Modelcited by 5
  31. 2025Adversarial Attacks Against Automated Fact-Checking: A Surveycited by 5
  32. 2021Modular Self-Supervision for Document-Level Relation Extractioncited by 4
  33. 2022Document-level Relation Extraction with Context Guided Mention Integration and Inter-pair Reasoningcited by 4
  34. 2022CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversationscited by 4
  35. 2022Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modelingcited by 4
  36. 2023Towards Integration of Discriminability and Robustness for Document-Level Relation Extractioncited by 4
  37. 2023A Comprehensive Survey of Document-level Relation Extraction (2016-2023)cited by 4
  38. 2023PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programmingcited by 4

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