🔗 Who cites «The Third PASCAL Recognizing Textual Entailment Challenge»

384 papers of our library cite it (of the 149,439 whose bibliographies we read) · 81 with a page here, the most cited first · ← back to «The Third PASCAL Recognizing Textual Entailment Challenge»

1. Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
2. RoBERTa: A Robustly Optimized BERT Pretraining ApproacharXiv:1907.11692Yinhan Liu, Myle Ott, Naman Goyal, et al.2019 · 9,837 citations
3. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language UnderstandingEMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLPAlex Wang, Amanpreet Singh, Julian Michael, et al.2018 · 7,276 citations
4. A large annotated corpus for learning natural language inferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Samuel R. Bowman, Gabor Angeli, Christopher Potts, et al.2015 · 5,299 citations
5. The Power of Scale for Parameter-Efficient Prompt TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Brian Lester, Rami Al-Rfou, Noah Constant2021 · 4,287 citations
6. Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,121 citations
7. ALBERT: A Lite BERT for Self-supervised Learning of Language RepresentationsarXiv:1909.11942Zhenzhong Lan, Mingda Chen, Sebastian Goodman, et al.2019 · 2,806 citations
8. SpanBERT: Improving Pre-training by Representing and Predicting SpansTransactions of the Association for Computational Linguistics (TACL)Mandar Joshi, Danqi Chen, Yinhan Liu, et al.2019 · 2,616 citations
9. SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding SystemsarXiv:1905.00537Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.2019 · 2,227 citations
10. Making Pre-trained Language Models Better Few-shot LearnersAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Adam Fisch, Danqi Chen2021 · 1,987 citations
11. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
12. DeBERTa: Decoding-enhanced BERT with Disentangled AttentionarXiv:2006.03654Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020 · 1,828 citations
13. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
14. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,444 citations
15. Unified Language Model Pre-training for Natural Language Understanding and GenerationarXiv:1905.03197Li Dong, Nan Yang, Wenhui Wang, et al.2019 · 1,422 citations
16. DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingarXiv:2111.09543Pengcheng He, Jianfeng Gao, Weizhu Chen2021 · 1,320 citations
17. The Stanford Typed Dependencies RepresentationMarie-Catherine de Marneffe, Christopher D. Manning2008 · 1,146 citations
18. AdapterHub: A Framework for Adapting TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, et al.2020 · 754 citations
19. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
20. Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timearXiv:2203.05482Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.2022 · 507 citations
21. LinkBERT: Pretraining Language Models with Document LinksAnnual Meeting of the Association for Computational Linguistics (ACL)Michihiro Yasunaga, Jure Leskovec, Percy Liang2022 · 458 citations
22. FreeLB: Enhanced Adversarial Training for Natural Language UnderstandingarXiv:1909.11764Chen Zhu, Yu Cheng, Zhe Gan, et al.2019 · 452 citations
23. True Few-Shot Learning with Language ModelsarXiv:2105.11447Ethan Perez, Douwe Kiela, Kyunghyun Cho2021 · 412 citations
24. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
25. UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingarXiv:2002.12804Hangbo Bao, Li Dong, Furu Wei, et al.2020 · 395 citations
26. SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Haoming Jiang, Pengcheng He, Weizhu Chen, et al.2020 · 304 citations
27. Finding Contradictions in TextAnnual Meeting of the Association for Computational Linguistics (ACL)Marie-Catherine de Marneffe, Anna N. Rafferty, Christopher D. Manning2008 · 300 citations
28. 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
29. BAM! Born-Again Multi-Task Networks for Natural Language UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal, et al.2019 · 285 citations
30. A Survey of Paraphrasing and Textual Entailment MethodsJournal of Artificial Intelligence ResearchIon Androutsopoulos, Prodromos Malakasiotis2009 · 284 citations
31. Paraphrase Identification as Probabilistic Quasi-Synchronous RecognitionAnnual Meeting of the Association for Computational Linguistics (ACL)Dipanjan Das, Noah A. Smith2009 · 278 citations
32. ZeroGen: Efficient Zero-shot Learning via Dataset GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Jiacheng Ye, Jiahui Gao, Qintong Li, et al.2022 · 245 citations
33. Coreferential Reasoning Learning for Language RepresentationConference on Empirical Methods in Natural Language Processing (EMNLP)Deming Ye, Yankai Lin, Jiaju Du, et al.2020 · 228 citations
34. Visualizing and Understanding the Effectiveness of BERTConference on Empirical Methods in Natural Language Processing (EMNLP)Yaru Hao, Li Dong, Furu Wei, et al.2019 · 222 citations
35. Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LuncharXiv:2311.03099Le Yu, Bowen Yu, Haiyang Yu, et al.2023 · 217 citations
36. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
37. Modality and Negation: An Introduction to the Special IssueComputational LinguisticsRoser Morante, Caroline Sporleder2012 · 205 citations
38. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
39. COCO-LM: Correcting and Contrasting Text Sequences for Language Model PretrainingarXiv:2102.08473Yu Meng, Chenyan Xiong, Payal Bajaj, et al.2021 · 198 citations
40. Paraphrasing for StyleWei Xu, Alan Ritter, Bill Dolan, et al.2012 · 196 citations
41. Debiasing Pre-trained Contextualised EmbeddingsConference of the European Chapter of the Association for Computational Linguistics (EACL)Masahiro Kaneko, Danushka Bollegala2021 · 175 citations
42. Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?Conference of the European Chapter of the Association for Computational Linguistics (EACL)Abhilasha Ravichander, Yonatan Belinkov, Eduard Hovy2021 · 144 citations
43. AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.2022 · 135 citations
44. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesarXiv:1904.01172Shane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 135 citations
45. The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning RepresentationsLasha Abzianidze, Johannes Bjerva, Kilian Evang, et al.2017 · 134 citations
46. An Analysis of Natural Language Inference Benchmarks through the Lens of NegationMd Mosharaf Hossain, Venelin Kovatchev, Pranoy Dutta, et al.2020 · 130 citations
47. Time Travel in LLMs: Tracing Data Contamination in Large Language ModelsarXiv:2308.08493Shahriar Golchin, Mihai Surdeanu2023 · 128 citations
48. EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language InferenceAbhilasha Ravichander, Aakanksha Naik, Carolyn Rose, et al.2019 · 123 citations
49. 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
50. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 121 citations
51. Inference is Everything: Recasting Semantic Resources into a Unified Evaluation FrameworkAaron Steven White, Pushpendre Rastogi, Kevin Duh, et al.2017 · 110 citations
52. “Ask Not What Textual Entailment Can Do for You...”Annual Meeting of the Association for Computational Linguistics (ACL)Mark Sammons, V.G.Vinod Vydiswaran, Dan Roth2010 · 108 citations
53. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
54. Understanding by Understanding Not: Modeling Negation in Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, et al.2021 · 98 citations
55. Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to QuestionsMichael Heilman, Noah A. Smith2010 · 87 citations
56. Generating Entailment Rules from FrameNetAnnual Meeting of the Association for Computational Linguistics (ACL)Roni Ben Aharon, Idan Szpektor, Ido Dagan2010 · 71 citations
57. Contradictions and Justifications: Extensions to the Textual Entailment TaskAnnual Meeting of the Association for Computational Linguistics (ACL)Ellen M. Voorhees2008 · 54 citations
58. Syntactic/Semantic Structures for Textual Entailment RecognitionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yashar Mehdad, Alessandro Moschitti, Fabio Massimo Zanzotto2010 · 43 citations
59. Inference Rules and their Application to Recognizing Textual EntailmentConference of the European Chapter of the Association for Computational Linguistics (EACL)Georgiana Dinu, Rui Wang2009 · 34 citations
60. Expanding textual entailment corpora fromWikipedia using co-trainingInternational Conference on Computational Linguistics (COLING)Fabio Massimo Zanzotto, Marco Pennacchiotti2010 · 33 citations
61. New Protocols and Negative Results for Textual Entailment Data CollectionConference on Empirical Methods in Natural Language Processing (EMNLP)Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.2020 · 27 citations
62. Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal NegationConference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)Hung Thinh Truong, Yulia Otmakhova, Timothy Baldwin, et al.2022 · 24 citations
63. Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual SettingsarXiv:2410.13153Krishno Dey, Prerona Tarannum, Md. Arid Hasan, et al.2024 · 16 citations
64. Curing the SICK and Other NLI MaladiesComputational LinguisticsAikaterini-Lida Kalouli, Hai Hu, Alexander F. Webb, et al.2023 · 14 citations
65. EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in EnglishFindings of the Association for Computational LinguisticsWeicheng Ma, Samiha Datta, Lili Wang, et al.2022 · 13 citations
66. 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
67. MEraser: An Effective Fingerprint Erasure Approach for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jingxuan Zhang, Zhenhua Xu, Rui Hu, et al.2025 · 11 citations
68. 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
69. Semantic Annotation of Textual EntailmentInternational Conference on Computational Semantics – Long PapersAssaf Toledo, Stavroula Alexandropoulou, Sophia Katrenko, et al.2013 · 7 citations
70. CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation BackdoorConference on Empirical Methods in Natural Language Processing (EMNLP)Zhenhua Xu, Xixiang Zhao, Xubin Yue, et al.2025 · 4 citations
71. Conditional Natural Language InferenceFindings of the Association for Computational LinguisticsYoungwoo Kim, Razieh Rahimi, James Allan2023 · 4 citations
72. NLI under the Microscope: What Atomic Hypothesis Decomposition RevealsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Neha Srikanth, Rachel Rudinger2025 · 3 citations
73. Corpora for Learning the Mutual Relationship between Semantic Relatedness and Textual EntailmentLanguage Resources and Evaluation Conference (LREC)Ngoc Phuoc An Vo, Octavian Popescu2016 · 3 citations
74. Why Do More Experts Fail? A Theoretical Analysis of Model MergingAnnual Meeting of the Association for Computational Linguistics (ACL)Zijing Wang, Xingle Xu, YongKang Liu, et al.2026 · 2 citations
75. Towards a Semantic Model for Textual Entailment AnnotationLinguistic Issues in Language TechnologyAssaf Toledo, Stavroula Alexandropoulou, Sophie Chesney, et al.2014 · 2 citations
76. Inference Rules for Recognizing Textual EntailmentInternational Conference on Computational SemanticsGeorgiana Dinu, Rui Wang2009 · 2 citations
77. Charting the European LLM Benchmarking Landscape: A New Taxonomy and RegistryShaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LRECSpela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.2026
78. E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference DatasetsIEEE AccessKhloud AL Jallad, Nada Ghneim, Ghaida Rebdawi2026
79. E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language UnderstandingarXiv:2609.33530Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi2026
80. Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid ArchitecturesFindings of the Association for Computational LinguisticsShenran Wang, Timothy Tin-Long Tse, Jian Zhu2026
81. A MISMATCHED Benchmark for Scientific Natural Language InferenceFindings of the Association for Computational LinguisticsFiroz Shaik, Mobashir Sadat, Nikita Gautam, et al.2025

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