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Who cites Aparajita Haldar

468 citations of their works from 442 papers of our library (of the 149,439 whose bibliographies we read) · 132 with a page here, the most cited first · page 2 of 2 · 101–132 · ← Aparajita Haldar

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  1. Curing the SICK and Other NLI MaladiesComputational LinguisticsAikaterini-Lida Kalouli, Hai Hu, Alexander F. Webb, et al.2023 · 14 citations
  2. Prompting for explanations improves Adversarial NLI. Is this true? \Yes\ it is \true\ because ıt weakens superficial cues\Findings of the Association for Computational LinguisticsPride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.2023 · 14 citations
  3. Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Sara Rajaee, Yadollah Yaghoobzadeh, Mohammad Taher Pilehvar2022 · 13 citations
  4. Partial-input baselines show that NLI models can ignore context, but they don't.Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Neha Srikanth, Rachel Rudinger2022 · 13 citations
  5. Towards the Necessity for Debiasing Natural Language Inference DatasetsLanguage Resources and Evaluation Conference (LREC)Mithun Paul Panenghat, Sandeep Suntwal, Faiz Rafique, et al.2020 · 13 citations
  6. Non-entailed subsequences as a challenge for natural language inferencearXiv:1811.12112R. Thomas McCoy, Tal Linzen2018 · 13 citations
  7. How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?Transactions of the Association for Computational Linguistics (TACL)Neha Srikanth, Marine Carpuat, Rachel Rudinger2024 · 10 citations
  8. A Generative Approach for Mitigating Structural Biases in Natural Language InferenceJoint Conference on Lexical and Computational Semantics (*SEM)Dimion Asael, Zachary Ziegler, Yonatan Belinkov2022 · 10 citations
  9. PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster OutliersConference of the European Chapter of the Association for Computational Linguistics (EACL)Michael Saxon, Xinyi Wang, Wenda Xu, et al.2023 · 9 citations
  10. Simple but Challenging: Natural Language Inference Models Fail on Simple SentencesFindings of the Association for Computational LinguisticsCheng Luo, Wei Liu, Jieyu Lin, et al.2022 · 7 citations
  11. Investigating Biases in Textual Entailment DatasetsarXiv:1906.09635Shawn Tan, Yikang Shen, Chin-wei Huang, et al.2019 · 7 citations
  12. Entailed Between the Lines: Incorporating Implication into NLIAnnual Meeting of the Association for Computational Linguistics (ACL)Shreya Havaldar, Hamidreza Alvari, John Palowitch, et al.2025 · 6 citations
  13. A Pragmatics-Centered Evaluation Framework for Natural Language UnderstandingLanguage Resources and Evaluation Conference (LREC)Damien Sileo, Philippe Muller, Tim Van de Cruys, et al.2022 · 6 citations
  14. SSR: Utilizing Simplified Stance Reasoning Process for Robust Stance DetectionInternational Conference on Computational Linguistics (COLING)Jianhua Yuan, Yanyan Zhao, Yanyue Lu, et al.2022 · 6 citations
  15. Annotation Difficulties in Natural Language InferenceBrazilian Symposium in Information and Human Language TechnologyAikaterini-Lida Kalouli, Livy Real, Annebeth Buis, et al.2021 · 5 citations
  16. How does Punctuation Affect Neural Models in Natural Language InferenceProceedings of the Probability and Meaning Conference (PaM 2020)Adam Ek, Jean-Philippe Bernardy, Stergios Chatzikyriakidis2020 · 4 citations
  17. How Hard is this Test Set? NLI Characterization by Exploiting Training DynamicsConference on Empirical Methods in Natural Language Processing (EMNLP)Adrian Cosma, Stefan Ruseti, Mihai Dascalu, et al.2024 · 3 citations
  18. No Context Needed: Contextual Quandary In Idiomatic Reasoning With Pre-Trained Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kellen Tan Cheng, Suma Bhat2024 · 3 citations
  19. Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning OptimizationLanguage Resources and Evaluation Conference (LREC)Michail Mersinias, Panagiotis Valvis2022 · 3 citations
  20. Hypothesis-only Biases in Large Language Model-Elicited Natural Language InferencearXiv:2410.08996Grace Proebsting, Adam Poliak2024 · 2 citations
  21. Investigating the Effect of Pre-finetuning BERT Models on NLI Involving PresuppositionsFindings of the Association for Computational LinguisticsJad Kabbara, Jackie Cheung2023 · 2 citations
  22. Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data SelectionFindings of the Association for Computational LinguisticsJoe Stacey, Lisa Alazraki, Aran Ubhi, et al.2026 · 1 citation
  23. Biases in Large Language Model-Elicited Text: A Case Study in Natural Language InferenceInternational Conference on Computational Linguistics (COLING)Grace Proebsting, Adam Poliak2025 · 1 citation
  24. On Reference (In-)Determinacy in Natural Language InferenceFindings of the Association for Computational LinguisticsSihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.2025 · 1 citation
  25. Exploiting Open IE for Deriving Multiple Premises Entailment CorpusRecent Advances in Natural Language Processing (RANLP)Martin Víta, Jakub Klímek2019 · 1 citation
  26. Computational models of pragmatic reasoning with flexible generation of meaning and expression alternativesarXiv:2607.18443Polina Tsvilodub, Fausto Carcassi, Michael Franke2026
  27. Explore Political Discourse with Transformers. Emergent Paradigmatic and Syntagmatic Representations.Language Resources and Evaluation Conference (LREC)Laurent Vanni, Damon Mayaffre2026
  28. Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation EntanglementAnnual Meeting of the Association for Computational Linguistics (ACL)Divyajot Singh2026
  29. The Validity of Coreference-based Evaluations of Natural Language UnderstandingarXiv:2602.16200Ian Porada2026
  30. Math Natural Language Inference: this should be easy!Joint Conference on Lexical and Computational Semantics (*SEM)Valeria de Paiva, Qiyue Gao, Hai Hu, et al.2025
  31. When Does Meaning Backfire? Investigating the Role of AMRs in NLIJoint Conference on Lexical and Computational Semantics (*SEM)Junghyun Min, Xiulin Yang, Shira Wein2025
  32. Exploring Lexical Irregularities in Hypothesis-Only Models of Natural Language InferencearXiv:2101.07397Qingyuan Hu, Yi Zhang, Kanishka Misra, et al.2021

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