CorefInst: Leveraging LLMs for Multilingual Coreference Resolution (2026.tacl-1)
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| Challenge: | Existing methods for CR are encoder-only, decoder-based and asynchronous models. |
| Approach: | They propose a multilingual CR methodology which leverages decoder-only LLMs to handle overt and zero mentions. |
| Outcome: | The proposed model outperforms the leading multilingual CR model by 2 percentage points across all languages in the CorefUD v1.2 dataset. |
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| Challenge: | a pretrained language model is used in state-of-the-art coreference resolution models. |
| Approach: | They evaluate five coreference resolution models and control for language model used . they find that encoder-based CR models outperform decoder--based models in accuracy . |
| Outcome: | The encoder-based model outperforms the decoder--based models in accuracy and speed . older model generalizes the best to out-of-domain textual genres . |
ImCoref-CeS: An Improved Lightweight Pipeline for Coreference Resolution with LLM-based Checker-Splitter Refinement (2026.acl-long)
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Kangyang Luo, Yuzhuo Bai, Shuzheng Si, Cheng Gao, Zhitong Wang, Yingli Shen, Wenhao Li, Zhu Liu, Yufeng Han, Jiayi Wu, Cunliang Kong, Maosong Sun
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Investigating Multilingual Coreference Resolution by Universal Annotations (2023.findings-emnlp)
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| Challenge: | Existing systems for multilingual coreference resolution have been challenging due to linguistic diversity and complexity of different languages. |
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Z-coref: Thai Coreference and Zero Pronoun Resolution (2024.acl-srw)
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| Challenge: | limited research and datasets pose significant challenges in Thai language . a proposed model capable of simultaneously handling CR and ZPR tasks takes less time to train . |
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Assessing the Capabilities of Large Language Models in Coreference: An Evaluation (2024.lrec-main)
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| Challenge: | Large Language Models (LLMs) are a new approach to coreference resolution, but their performance is not yet fully understood. |
| Approach: | They propose that future efforts should improve scope, data, and evaluation methods of traditional coreference research to adapt to the development of LLMs. |
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NovelCR: A Large-Scale Bilingual Dataset Tailored for Long-Span Coreference Resolution (2025.findings-acl)
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| Challenge: | Existing coreference resolution datasets are either small in scale or restrict coreference to a limited text span. |
| Approach: | They present a large-scale bilingual benchmark for long-span coreference resolution . they find that NovelCR is notably rich in long-spanning coreference pairs . |
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CorefUD 1.0: Coreference Meets Universal Dependencies (2022.lrec-1)
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| Challenge: | Recent advances in standardization for annotated language resources have led to successful large scale efforts, such as the Universal Dependencies (UD) project for multilingual syntactically annotized data. |
| Approach: | They propose a multilingual collection of corpora and a standardized format for coreference resolution compatible with morphosyntactic annotations in the UD framework. |
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Correct-Detect: Balancing Performance and Ambiguity Through the Lens of Coreference Resolution in LLMs (2025.emnlp-main)
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| Challenge: | Large Language Models (LLMs) are intended to reflect human linguistic competencies . but when context is absent or insufficient, ambiguity resolution becomes more tenuous . |
| Approach: | They propose a CORRECT-DETECT trade-off between large language models and ambiguity detection . they show that large language model models can achieve good performance with minimal prompting . |
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Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends (2024.acl-long)
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| Challenge: | Large autoregressive generative models have emerged as the cornerstone for achieving the highest performance across several Natural Language Processing tasks. |
| Approach: | They propose a pipeline that trains a state-of-the-art Coreference Resolution system within the constraints of an academic budget and trains with up to 0.006x the memory resources. |
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Coreference Resolution through a seq2seq Transition-Based System (2023.tacl-1)
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| Challenge: | Recent coreference resolution systems use search algorithms to identify mentions and resolve coreference. |
| Approach: | They propose a text-to-text coreference resolution system that uses a semantic paradigm to predict mentions and links jointly. |
| Outcome: | The proposed system achieves state-of-the-art accuracy on CoNLL-2012 datasets with 83.3 F1-score for English, 68.5 F1 score for Arabic, and 74.3 F1 scores for Chinese. |