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# Who cites «Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns»

142 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/webster-2018-mind-gap-balanced-corpus-gendered/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/webster-2018-mind-gap-balanced-corpus-gendered-2/)

1. [Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasing](https://aclanthology.org/2026.findings-acl.1668/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
2. [Gender Bias in MT for a Genderless Language: New Benchmarks for Basque](https://aclanthology.org/2026.lrec-1.705/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
3. [Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures](https://aclanthology.org/2026.lrec-1.673/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
4. [Not All Disneys Are the Same: Making Coreference Metonymy-Aware](https://aclanthology.org/2026.lrec-1.941/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
5. [The Validity of Coreference-based Evaluations of Natural Language Understanding](https://arxiv.org/abs/2602.16200) *— 2026 · arXiv:2602.16200*
6. [Bridge the GAP: Multi-lingual Models For Ambiguous Pronominal Coreference Resolution in South Asian Languages](https://aclanthology.org/2025.chipsal-1.10/) *— 2025 · Proceedings of the First Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2025)*
7. [Enhancing Coreference Resolution with LLM-driven Data Augmentation and Adversarial Filtering](https://aclanthology.org/2025.findings-ijcnlp.56/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
8. [HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America](https://aclanthology.org/2025.emnlp-main.1275/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
9. [Investigating the Capabilities and Limitations of Machine Learning for Identifying Bias in English Language Data with Information and Heritage Professionals](https://arxiv.org/abs/2504.00860) *— 2025 · arXiv:2504.00860*
10. [LLM Bias Detection and Mitigation through the Lens of Desired Distributions](https://aclanthology.org/2025.emnlp-main.76/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
11. [LLMs on Trial: Evaluating Judicial Fairness for Large Language Models](https://arxiv.org/abs/2507.10852) *— 2025 · arXiv:2507.10852*
12. [Large Language Models Still Exhibit Bias in Long Text](https://aclanthology.org/2025.findings-acl.1341/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
13. [Multimodal Coreference Resolution for Chinese Social Media Dialogues: Dataset and Benchmark Approach](https://aclanthology.org/2025.acl-long.1520/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs](https://aclanthology.org/2025.naacl-long.29/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
15. [Overview of the NLPCC 2025 Shared Task: Gender Bias Mitigation Challenge](https://arxiv.org/abs/2506.12574) *— 2025 · arXiv:2506.12574*
16. [Towards Region-aware Bias Evaluation Metrics](https://aclanthology.org/2025.c3nlp-1.9/) *— 2025 · Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025)*
17. [A Controlled Reevaluation of Coreference Resolution Models](https://aclanthology.org/2024.lrec-main.23/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
18. [Bias in Large Language Models: Origin, Evaluation, and Mitigation](https://arxiv.org/abs/2411.10915) *— 2024 · arXiv:2411.10915*
19. [Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective](https://md.mova.elamur.ai/free/en/docs/papers/porada-2024-challenges-evaluating-generalization-coreference-resolution/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
20. [La recherche sur les biais dans les modèles de langue est biaisée : état de l''art en abyme Bias Research for Language Models is Biased: a Survey for Deconstructing Bias in Large Language Models](https://aclanthology.org/2023.tal-3.6/) *— 2024*
21. [Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends](https://aclanthology.org/2024.acl-long.722/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [Robust Pronoun Fidelity with English LLMs: Are they Reasoning, Repeating, or Just Biased?](https://aclanthology.org/2024.tacl-1.95/) *— 2024*
23. [Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution](https://aclanthology.org/2024.conll-1.38/) *— 2024 · Proceedings of the 28th Conference on Computational Natural Language Learning*
24. [The ARRAU 3.0 Corpus](https://aclanthology.org/2024.codi-1.12/) *— 2024 · Proceedings of the 5th Workshop on Computational Approaches to Discourse (CODI 2024)*
25. [Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions](https://aclanthology.org/2024.findings-emnlp.545/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
26. [Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns](https://arxiv.org/abs/2405.00134) *— 2024 · arXiv:2405.00134*
27. [Universal Anaphora: The First Three Years](https://aclanthology.org/2024.lrec-main.1484/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
28. [AI Alignment: A Comprehensive Survey](https://arxiv.org/abs/2310.19852) *— 2023 · arXiv:2310.19852*
29. [Bias and Fairness in Large Language Models: A Survey](https://arxiv.org/abs/2309.00770) *— 2023 · arXiv:2309.00770*
30. [Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns](https://aclanthology.org/2023.eacl-main.272/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
31. [Ensemble Transfer Learning for Multilingual Coreference Resolution](https://aclanthology.org/2023.codi-1.3/) *— 2023 · Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023)*
32. [Evaluating Large Language Models: A Comprehensive Survey](https://arxiv.org/abs/2310.19736) *— 2023 · arXiv:2310.19736*
33. [GPT-4 Technical Report](https://arxiv.org/abs/2303.08774) *— 2023 · arXiv:2303.08774*
34. [Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting](https://aclanthology.org/2023.acl-short.108/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
35. [LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution](https://md.mova.elamur.ai/free/en/docs/papers/otmazgin-2023-lingmess-linguistically-informed-multi-expert/) *— our card · 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
36. [McGill at CRAC 2023: Multilingual Generalization of Entity-Ranking Coreference Resolution Models](https://aclanthology.org/2023.crac-sharedtask.5/) *— 2023 · Proceedings of the CRAC 2023 Shared Task on Multilingual Coreference Resolution*
37. [Measuring Gender Bias in Natural Language Processing: Incorporating Gender-Neutral Linguistic Forms for Non-Binary Gender Identities in Abusive Speech Detection](https://aclanthology.org/2023.ranlp-1.119/) *— 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing*
38. [Measuring Gender Bias in West Slavic Language Models](https://aclanthology.org/2023.bsnlp-1.17/) *— 2023 · Proceedings of the 9th Workshop on Slavic Natural Language Processing 2023 (SlavicNLP 2023)*
39. [Prompting with Pseudo-Code Instructions](https://aclanthology.org/2023.emnlp-main.939/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
40. [Scoring Coreference Chains with Split-Antecedent Anaphors](https://md.mova.elamur.ai/free/en/docs/papers/paun-2023-scoring-coreference-chains-split-antecedent/) *— our card · 2023*
41. [Sociodemographic Bias in Language Models: A Survey and Forward Path](https://arxiv.org/abs/2306.08158) *— 2023 · arXiv:2306.08158*
42. [The KITMUS Test: Evaluating Knowledge Integration from Multiple Sources](https://aclanthology.org/2023.acl-long.841/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
43. [The pragmatics of characters' mental perspectives in pronominal reference resolution](https://aclanthology.org/2023.crac-main.6/) *— 2023 · Proceedings of the Sixth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC 2023)*
44. [What social attitudes about gender does BERT encode? Leveraging insights from psycholinguistics](https://aclanthology.org/2023.acl-long.375/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [With Prejudice to None: A Few-Shot, Multilingual Transfer Learning Approach to Detect Social Bias in Low Resource Languages](https://aclanthology.org/2023.findings-acl.842/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
46. [``Fifty Shades of Bias'''': Normative Ratings of Gender Bias in GPT Generated English Text](https://aclanthology.org/2023.emnlp-main.115/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
47. [BBQ: A hand-built bias benchmark for question answering](https://aclanthology.org/2022.findings-acl.165/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
48. [Bias Identification and Attribution in NLP Models With Regression and Effect Sizes](https://nejlt.ep.liu.se/article/view/3505) *— 2022 · Northern European Journal of Language Technology*
49. [Choose Your Lenses: Flaws in Gender Bias Evaluation](https://aclanthology.org/2022.gebnlp-1.17/) *— 2022 · Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (GeBNLP)*
50. [Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language Understanding](https://aclanthology.org/2022.naacl-main.234/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
51. [F-coref: Fast, Accurate and Easy to Use Coreference Resolution](https://aclanthology.org/2022.aacl-demo.6/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: System Demonstrations*
52. [Hollywood Identity Bias Dataset: A Context Oriented Bias Analysis of Movie Dialogues](https://aclanthology.org/2022.lrec-1.565/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
53. [How Conservative are Language Models? Adapting to the Introduction of Gender-Neutral Pronouns](https://aclanthology.org/2022.naacl-main.265/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
54. [How Gender Debiasing Affects Internal Model Representations, and Why It Matters](https://aclanthology.org/2022.naacl-main.188/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
55. [Incorporating Centering Theory into Neural Coreference Resolution](https://aclanthology.org/2022.naacl-main.218/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
56. [Inferring Gender: A Scalable Methodology for Gender Detection with Online Lexical Databases](https://aclanthology.org/2022.ltedi-1.7/) *— 2022 · Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion*
57. [Measuring Fairness with Biased Rulers: A Comparative Study on Bias Metrics for Pre-trained Language Models](https://aclanthology.org/2022.naacl-main.122/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
58. [NARC – Norwegian Anaphora Resolution Corpus](https://aclanthology.org/2022.crac-1.6/) *— 2022 · Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference*
59. [On Measures of Biases and Harms in NLP](https://aclanthology.org/2022.findings-aacl.24/) *— 2022 · Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022*
60. [Quantifying Bias from Decoding Techniques in Natural Language Generation](https://aclanthology.org/2022.coling-1.112/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
61. [Sentence-Incremental Neural Coreference Resolution](https://aclanthology.org/2022.emnlp-main.28/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
62. [The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue](https://md.mova.elamur.ai/free/en/docs/papers/yu-2022-codi-crac-2022-shared-task/) *— our card · 2022 · Proceedings of the CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue*
63. [The Universal Anaphora Scorer](https://aclanthology.org/2022.lrec-1.521/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
64. [Uncertainty and Inclusivity in Gender Bias Annotation: An Annotation Taxonomy and Annotated Datasets of British English Text](https://aclanthology.org/2022.gebnlp-1.4/) *— 2022 · Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (GeBNLP)*
65. [Welcome to the Modern World of Pronouns: Identity-Inclusive Natural Language Processing beyond Gender](https://aclanthology.org/2022.coling-1.105/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
66. [A Hybrid Rule-Based and Neural Coreference Resolution System with an Evaluation on Dutch Literature](https://aclanthology.org/2021.crac-1.5/) *— 2021 · Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference*
67. [Adapting Coreference Resolution for Processing Violent Death Narratives](https://aclanthology.org/2021.naacl-main.361/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
68. [Anatomy of OntoGUM–-Adapting GUM to the OntoNotes Scheme to Evaluate Robustness of SOTA Coreference Algorithms](https://md.mova.elamur.ai/free/en/docs/papers/zhu-2021-anatomy-ontogum-adapting-gum-ontonotes/) *— our card · 2021 · Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference*
69. [Annotation and Evaluation of Coreference Resolution in Screenplays](https://aclanthology.org/2021.findings-acl.176/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
70. [Assessing Gender Bias in Wikipedia: Inequalities in Article Titles](https://aclanthology.org/2021.gebnlp-1.9/) *— 2021 · Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing*
71. [Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation](https://aclanthology.org/2021.findings-emnlp.211/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
72. [Coreference Resolution without Span Representations](https://aclanthology.org/2021.acl-short.3/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
73. [Coreference meets Universal Dependencies – a pilot experiment on harmonizing coreference datasets for 11 languages](https://md.mova.elamur.ai/free/en/docs/papers/nedoluzhko-2021-coreference-meets-universal-dependencies/) *— our card · 2021 · ÚFAL Technical Report TR-2021-66 (ISSN 1214-5521)*
74. [Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies](https://aclanthology.org/2021.emnlp-main.150/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
75. [Modeling Coreference Relations in Visual Dialog](https://aclanthology.org/2021.eacl-main.290/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
76. [Moving on from OntoNotes: Coreference Resolution Model Transfer](https://aclanthology.org/2021.emnlp-main.425/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
77. [OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings](https://aclanthology.org/2021.emnlp-main.411/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
78. [On Generalization in Coreference Resolution](https://md.mova.elamur.ai/free/en/docs/papers/toshniwal-2021-generalization-coreference-resolution/) *— our card · 2021 · Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference*
79. [OntoGUM: Evaluating Contextualized SOTA Coreference Resolution on 12 More Genres](https://aclanthology.org/2021.acl-short.59/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
80. [Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics](https://aclanthology.org/2021.tacl-1.74/) *— 2021 · Transactions of the Association for Computational Linguistics*
81. [Stay Together: A System for Single and Split-antecedent Anaphora Resolution](https://aclanthology.org/2021.naacl-main.329/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
82. [Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you?](https://aclanthology.org/2021.emnlp-main.111/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
83. [Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models](https://aclanthology.org/2021.eacl-main.190/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
84. [The Swedish Winogender Dataset](https://aclanthology.org/2021.nodalida-main.52/) *— 2021 · Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)*
85. [They, Them, Theirs: Rewriting with Gender-Neutral English](https://arxiv.org/abs/2102.06788) *— 2021 · arXiv:2102.06788*
86. [Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy](https://aclanthology.org/2021.emnlp-main.444/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
87. [Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle*](https://aclanthology.org/2021.cl-3.19/) *— 2021*
88. [Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models](https://aclanthology.org/2021.emnlp-main.688/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
89. [Unsupervised Pronoun Resolution via Masked Noun-Phrase Prediction](https://aclanthology.org/2021.acl-short.117/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
90. [gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena](https://aclanthology.org/2021.gebnlp-1.1/) *— 2021 · Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing*
91. [A Framework for Evaluation of Machine Reading Comprehension Gold Standards](https://aclanthology.org/2020.lrec-1.660/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
92. [A Neural Model for Aggregating Coreference Annotation in Crowdsourcing](https://aclanthology.org/2020.coling-main.507/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
93. [CLUE: A Chinese Language Understanding Evaluation Benchmark](https://arxiv.org/abs/2004.05986) *— 2020 · arXiv:2004.05986*
94. [CorefQA: Coreference Resolution as Query-based Span Prediction](https://aclanthology.org/2020.acl-main.622/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
95. [Coreferential Reasoning Learning for Language Representation](https://aclanthology.org/2020.emnlp-main.582/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
96. [CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://aclanthology.org/2020.emnlp-main.154/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
97. [Demoting Racial Bias in Hate Speech Detection](https://aclanthology.org/2020.socialnlp-1.2/) *— 2020 · Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media*
98. [Enhanced Labelling in Active Learning for Coreference Resolution](https://aclanthology.org/2020.crac-1.12/) *— 2020 · Proceedings of the Third Workshop on Computational Models of Reference, Anaphora and Coreference*
99. [Fast End-to-end Coreference Resolution for Korean](https://aclanthology.org/2020.findings-emnlp.237/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
100. [Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution](https://md.mova.elamur.ai/free/en/docs/papers/yu-2020-free-plural-unrestricted-split-antecedent/) *— our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics*

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