# Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering

arXiv: https://arxiv.org/abs/1805.04893 · HTML: https://mlsanity.com/paper/1805.04893/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 May 2018.

## Built on by (most cited first, 16 of 16)

- [On Generalization in Coreference Resolution](https://mlsanity.com/paper/2109.09667/) (2021)
- [Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends](https://mlsanity.com/paper/2407.21489/) (2024)
- [Moving on from OntoNotes: Coreference Resolution Model Transfer](https://mlsanity.com/paper/2104.08457/) (2021)
- [End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline](https://mlsanity.com/paper/2107.01700/) (2021)
- [Any Other Thoughts, Hedgehog? Linking Deliberation Chains in Collaborative Dialogues](https://mlsanity.com/paper/2410.19301/) (2024)
- [Can we Fix the Scope for Coreference? Problems and Solutions for Benchmarks beyond OntoNotes](https://mlsanity.com/paper/2112.09742/) (2021)
- [A Survey on Semantic Processing Techniques](https://mlsanity.com/paper/2310.18345/) (2023)
- [A Structured Span Selector](https://mlsanity.com/paper/2205.03977/) (2022)
- [A hybrid entity-centric approach to Persian pronoun resolution](https://mlsanity.com/paper/2211.06257/) (2022)
- [Pro-HAN: A Heterogeneous Graph Attention Network for Profile-Based Spoken Language Understanding](https://mlsanity.com/paper/2402.03900/) (2024)
- [Hybrid Rule-Neural Coreference Resolution System based on Actor-Critic Learning](https://mlsanity.com/paper/2212.10087/) (2022)
- [Coreference Resolution: Are the eliminated spans totally worthless?](https://mlsanity.com/paper/2101.00737/) (2021)
- [Review of coreference resolution in English and Persian](https://mlsanity.com/paper/2211.04428/) (2022)
- [Neural Coreference Resolution based on Reinforcement Learning](https://mlsanity.com/paper/2212.09028/) (2022)
- [Persian Pronoun Resolution: Leveraging Neural Networks and Language Models](https://mlsanity.com/paper/2405.10714/) (2024)
- [From Inline Notes to Collected Commentaries: Toward Context-Preserving Organization of Exegetical Knowledge in Classical Chinese Texts](https://mlsanity.com/paper/2607.29044/) (2026)

## Abstract (arXiv)

Coreference resolution aims to identify in a text all mentions that refer to the same real-world entity. The state-of-the-art end-to-end neural coreference model considers all text spans in a document as potential mentions and learns to link an antecedent for each possible mention. In this paper, we propose to improve the end-to-end coreference resolution system by (1) using a biaffine attention model to get antecedent scores for each possible mention, and (2) jointly optimizing the mention detection accuracy and the mention clustering log-likelihood given the mention cluster labels. Our model achieves the state-of-the-art performance on the CoNLL-2012 Shared Task English test set.