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Who cites «Hypothesis Only Baselines in Natural Language Inference»

377 papers of our library cite it (of the 149,439 whose bibliographies we read) · 113 with a page here, the most cited first · page 2 of 2 · 101–113 · ← back to «Hypothesis Only Baselines in Natural Language Inference»

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  1. 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
  2. Hypothesis-only Biases in Large Language Model-Elicited Natural Language InferencearXiv:2410.08996Grace Proebsting, Adam Poliak2024 · 2 citations
  3. Investigating the Effect of Pre-finetuning BERT Models on NLI Involving PresuppositionsFindings of the Association for Computational LinguisticsJad Kabbara, Jackie Cheung2023 · 2 citations
  4. 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
  5. 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
  6. On Reference (In-)Determinacy in Natural Language InferenceFindings of the Association for Computational LinguisticsSihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.2025 · 1 citation
  7. Exploiting Open IE for Deriving Multiple Premises Entailment CorpusRecent Advances in Natural Language Processing (RANLP)Martin Víta, Jakub Klímek2019 · 1 citation
  8. Computational models of pragmatic reasoning with flexible generation of meaning and expression alternativesarXiv:2607.18443Polina Tsvilodub, Fausto Carcassi, Michael Franke2026
  9. Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation EntanglementAnnual Meeting of the Association for Computational Linguistics (ACL)Divyajot Singh2026
  10. The Validity of Coreference-based Evaluations of Natural Language UnderstandingarXiv:2602.16200Ian Porada2026
  11. 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
  12. When Does Meaning Backfire? Investigating the Role of AMRs in NLIJoint Conference on Lexical and Computational Semantics (*SEM)Junghyun Min, Xiulin Yang, Shira Wein2025
  13. 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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264 more papers of our library cite it; they have no page here yet.

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