CAW-coref: Conjunction-Aware Word-level Coreference Resolution
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Abstract (arXiv)
State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are thus prohibitively expensive for many use cases (e.g., information extraction with large corpora). The leading word-level coreference system (WL-coref) attains 96.6% of these SOTA systems' performance while being much more efficient. In this work, we identify a routine yet important failure case of WL-coref: dealing with conjoined mentions such as 'Tom and Mary'. We offer a simple yet effective solution that improves the performance on the OntoNotes test set by 0.9% F1, shrinking the gap between efficient word-level coreference resolution and expensive SOTA approaches by 34.6%. Our Conjunction-Aware Word-level coreference model (CAW-coref) and code is available at https://github.com/KarelDO/wl-coref.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 13 of its 25 references that are in the map. First posted on arXiv 9 Oct 2023.
Builds on
13 of 25 references.
References · 13
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
- 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,813
- 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
- 2017End-to-end Neural Coreference Resolutioncited by 240
- 2018Higher-order Coreference Resolution with Coarse-to-fine Inferencecited by 150
- 2019Coreference Resolution as Query-based Span Predictioncited by 91
- 2022Autoregressive Structured Prediction with Language Modelscited by 43
- 2021Word-Level Coreference Resolutioncited by 40
- 2022Coreference Resolution through a seq2seq Transition-Based Systemcited by 34
- 2022LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolutioncited by 26
- 2022F-coref: Fast, Accurate and Easy to Use Coreference Resolutioncited by 23
Built on by
Citing papers per year: 2024: 4; 2025: 4; 2026: 2.
10 papers.
- 2024WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical Casecited by 9
- 2024CorPipe at CRAC 2024: Predicting Zero Mentions from Raw Textcited by 6
- 2025GUM-SAGE: A Novel Dataset and Approach for Graded Entity Salience Predictioncited by 6
- 2025Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?cited by 5
- 2024Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUDcited by 3
- 2025CorPipe at CRAC 2025: Evaluating Multilingual Encoders for Multilingual Coreference Resolutioncited by 2
- 2026Pantagruel: Unified Self-Supervised Encoders for French Text and Speechcited by 2
- 2024ThaiCoref: Thai Coreference Resolution Datasetcited by 0
- 2025CorefInst: Leveraging LLMs for Multilingual Coreference Resolutioncited by 0
- 2026CorPipe at CRAC 2026: Empty Nodes and Cross-Lingual Transfer in Multilingual Coreference Resolutioncited by 0
- 2026CorPipe at CRAC 2026: Empty Nodes and Cross-Lingual Transfer in Multilingual Coreference Resolution28 May 2026
- 2026Pantagruel: Unified Self-Supervised Encoders for French Text and Speech9 Jan 2026
- 2025CorPipe at CRAC 2025: Evaluating Multilingual Encoders for Multilingual Coreference Resolution22 Sep 2025
- 2025Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?22 Sep 2025
- 2025CorefInst: Leveraging LLMs for Multilingual Coreference Resolution22 Sep 2025
- 2025GUM-SAGE: A Novel Dataset and Approach for Graded Entity Salience Prediction15 Apr 2025
- 2024CorPipe at CRAC 2024: Predicting Zero Mentions from Raw Text3 Oct 2024
- 2024WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical Case9 Sep 2024
- 2024Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUD29 Aug 2024
- 2024ThaiCoref: Thai Coreference Resolution Dataset10 Jun 2024