🔗 Who cites «Transforming Question Answering Datasets Into Natural Language Inference Datasets»

107 papers of our library cite it (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← back to «Transforming Question Answering Datasets Into Natural Language Inference Datasets»

1. BoolQ: Exploring the Surprising Difficulty of Natural Yes/No QuestionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Christopher Clark, Kenton Lee, Ming-Wei Chang, et al.2019 · 1,330 citations
2. Dialogue Natural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Sean Welleck, Jason Weston, Arthur Szlam, et al.2019 · 385 citations
3. FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive SummarizationAnnual Meeting of the Association for Computational Linguistics (ACL)Esin Durmus, He He, Mona Diab2020 · 359 citations
4. Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for LittleConference on Empirical Methods in Natural Language Processing (EMNLP)Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.2021 · 297 citations
5. QAFactEval: Improved QA-Based Factual Consistency Evaluation for SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.2022 · 292 citations
6. AlignScore: Evaluating Factual Consistency with A Unified Alignment FunctionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuheng Zha, Yichi Yang, Ruichen Li, et al.2023 · 284 citations
7. Explaining Answers with Entailment TreesConference on Empirical Methods in Natural Language Processing (EMNLP)Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, et al.2021 · 211 citations
8. DART: Open-Domain Structured Data Record to Text GenerationarXiv:2007.02871Linyong Nan, Dragomir Radev, Rui Zhang, et al.2020 · 161 citations
9. Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a SummaryTransactions of the Association for Computational Linguistics (TACL)Daniel Deutsch, Tania Bedrax-Weiss, Dan Roth2021 · 152 citations
10. ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft PromptsConference on Empirical Methods in Natural Language Processing (EMNLP)Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.2022 · 122 citations
11. Entailer: Answering Questions with Faithful and Truthful Chains of ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Oyvind Tafjord, Bhavana Dalvi Mishra, Peter Clark2022 · 71 citations
12. ANLIzing the Adversarial Natural Language Inference DatasetSociety for Computation in Linguistics (SCiL)Adina Williams, Tristan Thrush, Douwe Kiela2022 · 48 citations
13. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataFindings of the Association for Computational LinguisticsMubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.2023 · 38 citations
14. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and modelsarXiv:2005.14709Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro2020 · 24 citations
15. Enhancing Systematic Decompositional Natural Language Inference Using Informal LogicConference on Empirical Methods in Natural Language Processing (EMNLP)Nathaniel Weir, Kate Sanders, Orion Weller, et al.2024 · 7 citations
16. Evaluating Numeracy of Language Models as a Natural Language Inference TaskFindings of the Association for Computational LinguisticsRahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.2025 · 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. Understanding Roles and Entities: Datasets and Models for Natural Language InferencearXiv:1904.09720Arindam Mitra, Ishan Shrivastava, Chitta Baral2019 · 2 citations
19. Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order InteractionsFindings of the Association for Computational LinguisticsWenhao Zhang, Lin Mu, Li Ni, et al.2026 · 1 citation
20. From Multiple-Choice to Extractive QA: A Case Study for English and ArabicInternational Conference on Computational Linguistics (COLING)Teresa Lynn, Malik H. Altakrori, Samar M. Magdy, et al.2025 · 1 citation
21. Specialization without Sparsity: Efficient and Expressive Split-Path Experts for LLM Fine-TuningFindings of the Association for Computational LinguisticsGanghao Liu, Qin Zhou, Zhe Wang, et al.2026
22. Ultra-Low-Dimensional Prompt Tuning via Random ProjectionConference of the European Chapter of the Association for Computational Linguistics (EACL)Zijun Wu, Yongchang Hao, Lili Mou2026
23. Can predicate-argument relationships be extracted from UD trees?Adam Ek, Jean-Philippe Bernardy, Stergios Chatzikyriakidis2021

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