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 .
Outcome: The proposed benchmark is rich in long-span coreference pairs and notably low baselines.

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BOOKCOREF: Coreference Resolution at Book Scale (2025.acl-long)

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Challenge: Existing benchmarks for coreference resolution systems are limited in length and do not adequately assess system capabilities at the book scale.
Approach: They propose a novel pipeline that produces high-quality coreference resolution annotations on full narrative texts and a book-scale benchmark, BOOKCOREF.
Outcome: The proposed pipeline produces high-quality coreference resolution annotations on full texts with an average document length of more than 200,000 tokens.
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.
Beyond Word Boundaries: A Hebrew Coreference Benchmark and an Evaluation Protocol for Morphologically Complex Text (2026.acl-long)

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Challenge: CR methods originally designed for English struggle with Morphologically Rich Languages (MRLs) a single token in Hebrew may consist of multiple anaphors, and word/morpheme boundary discrepancies make mention detection and coreference resolution difficult in MRLs.
Approach: They propose a CR dataset that identifies mentions at word, sub-word and multi-word levels and an evaluation protocol that directly addresses word/morpheme boundary discrepancies.
Outcome: The proposed evaluation protocol directly addresses word/morpheme boundary discrepancies in Modern Hebrew, an MRL rich with complex words and pronominal clitics.
Multilingual Coreference Resolution in Multiparty Dialogue (2023.tacl-1)

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Challenge: Existing datasets for entity coreference resolution are limited to English and other languages are rare.
Approach: They propose to use TV transcripts to create multilingual multiparty coreference datasets that leverage existing subtitles in Chinese and Farsi.
Outcome: The proposed dataset re-annotates for coreference on TV transcripts and then leverages existing subtitle translations to create a multilingual corpus.
WikiCREM: A Large Unsupervised Corpus for Coreference Resolution (D19-1)

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Challenge: Large-scale training sets for pronoun resolution are scarce, since manually labelling data is costly.
Approach: They propose a language-model-based approach to solve pronoun disambiguation problems using a WikiCREM dataset.
Outcome: The proposed model outperforms state-of-the-art approaches on 6 out of 7 datasets.
Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance (2021.naacl-main)

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Challenge: Recent work on entity coreference resolution (CR) follows current trends in Deep Learning . traditional approaches do not make use of hierarchical representations of discourse structure .
Approach: They propose to leverage automatically constructed discourse parse trees within a neural approach to generate anaphoric mentions.
Outcome: The proposed model improves on two benchmark entity coreference-resolution datasets.
PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution (D18-1)

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Challenge: Existing methods for coreference resolution are based on word2vec-like representations of entities.
Approach: They propose a large-scale English dataset for coreference resolution . they use 38K documents and 12.5M words from English-speaking preschoolers .
Outcome: The proposed dataset is more efficient with higher training-test overlap than OntoNotes . the study also shows that mention detection and clustering are more efficient on PreCo .
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.
Outcome: The proposed framework is compatible with morphosyntactic annotations and includes facilities for related tasks such as named entity recognition.
ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution (2023.findings-eacl)

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Challenge: Existing datasets vary in definition of coreferences and are curated for linguistic experts.
Approach: They propose to use ezCoref to create a crowdsourcing-friendly coreference annotation methodology that teaches annotators only cases that are treated similarly across existing datasets.
Outcome: The proposed method reannotates 240 passages from seven existing english coreference datasets while teaching annotators only cases that are treated similarly across them.
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 .
Approach: They propose to annotate a Thai-based CR and ZPR dataset and introduce a model that can handle both tasks by adjusting the span definition to include token gaps.
Outcome: The proposed model outperforms the state-of-the-art in resolving both coreference resolution and zero-pronoun resolution while taking less time to train.

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