---
title: "Who cites Bernardo Magnini — page 2 — 1,197 citing papers"
description: "1,197 papers of the Elamur Research library cite the works of Bernardo Magnini, found in their bibliographies · page 2 of 3 · 101–200; the…"
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---
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# Who cites Bernardo Magnini

1,454 citations of their works from 1,197 papers of our library (of the 141,840 whose bibliographies we read) · 201 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Bernardo Magnini](https://md.research.elamur.ai/free/en/authors/bernardo-magnini/)

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101. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
102. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
103. [**Paraphrasing for Style**Wei Xu, Alan Ritter, Bill Dolan, et al.*2012 · 196 citations*](https://md.research.elamur.ai/free/en/papers/xu-2012-paraphrasing-style/)
104. **[Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering](https://md.research.elamur.ai/free/en/papers/honovich-2021-q-2-evaluating-factual-consistency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Or Honovich, Leshem Choshen, Roee Aharoni, et al.*2021 · 195 citations*
105. **[The Right Tool for the Job: Matching Model and Instance Complexities](https://md.research.elamur.ai/free/en/papers/schwartz-2020-right-tool-job-matching-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, et al.*2020 · 194 citations*
106. [**Making Retrieval-Augmented Language Models Robust to Irrelevant Context arXiv:2310.01558**Ori Yoran, Tomer Wolfson, Ori Ram, et al.*2023 · 193 citations*](https://md.research.elamur.ai/free/en/papers/yoran-2023-making-retrieval-augmented-language-models/)
107. **[Exploring and Predicting Transferability across NLP Tasks](https://md.research.elamur.ai/free/en/papers/vu-2020-exploring-predicting-transferability-across-nlp/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tu Vu, Tong Wang, Tsendsuren Munkhdalai, et al.*2020 · 192 citations*
108. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 191 citations*
109. [**Computing relative polarity for textual inference**Rowan Nairn, Cleo Condoravdi, Lauri Karttunen*2006 · 191 citations*](https://md.research.elamur.ai/free/en/papers/nairn-2006-computing-relative-polarity-textual-inference/)
110. **[Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation](https://md.research.elamur.ai/free/en/papers/poliak-2018-collecting-diverse-natural-language-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adam Poliak, Aparajita Haldar, Rachel Rudinger, et al.*2018 · 190 citations*
111. **[Adapting Language Models to Compress Contexts](https://md.research.elamur.ai/free/en/papers/chevalier-2023-adapting-language-models-compress-contexts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.*2023 · 179 citations*
112. **[What Makes Reading Comprehension Questions Easier?](https://md.research.elamur.ai/free/en/papers/sugawara-2018-what-makes-reading-comprehension-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.*2018 · 178 citations*
113. **[Debiasing Pre-trained Contextualised Embeddings](https://md.research.elamur.ai/free/en/papers/kaneko-2021-debiasing-pre-trained-contextualised-embeddings/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Masahiro Kaneko, Danushka Bollegala*2021 · 174 citations*
114. **[Reasoning Over Paragraph Effects in Situations](https://md.research.elamur.ai/free/en/papers/lin-2019-reasoning-over-paragraph-effects-situations/) [Workshop on Machine Reading for Question Answering](https://md.research.elamur.ai/free/en/venues/mrqa/)**Kevin Lin, Oyvind Tafjord, Peter Clark, et al.*2019 · 174 citations*
115. **[Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction](https://md.research.elamur.ai/free/en/papers/sainz-2021-label-verbalization-entailment-effective-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, et al.*2021 · 167 citations*
116. **[Generating Coherent Event Schemas at Scale](https://md.research.elamur.ai/free/en/papers/balasubramanian-2013-generating-coherent-event-schemas-scale/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niranjan Balasubramanian, Stephen Soderland, Mausam, et al.*2013 · 165 citations*
117. [**Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition**Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan, et al.*2020 · 161 citations*](https://md.research.elamur.ai/free/en/papers/jeretic-2020-are-natural-language-inference-models/)
118. **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations*
119. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation arXiv:2305.15852**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
120. **[INFOTABS: Inference on Tables as Semi-structured Data](https://md.research.elamur.ai/free/en/papers/gupta-2020-infotabs-inference-tables-as-semi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vivek Gupta, Maitrey Mehta, Pegah Nokhiz, et al.*2020 · 150 citations*
121. **[Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks](https://md.research.elamur.ai/free/en/papers/dou-2019-investigating-meta-learning-algorithms-low/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zi-Yi Dou, Keyi Yu, Antonios Anastasopoulos*2019 · 150 citations*
122. **[HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment](https://md.research.elamur.ai/free/en/papers/vulic-2017-hyperlex-large-scale-evaluation-graded/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ivan Vulić, Daniela Gerz, Douwe Kiela, et al.*2017 · 148 citations*
123. **[Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation](https://md.research.elamur.ai/free/en/papers/mosbach-2023-few-shot-fine-tuning-vs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Marius Mosbach, Tiago Pimentel, Shauli Ravfogel, et al.*2023 · 147 citations*
124. **[Full Parameter Fine-tuning for Large Language Models with Limited Resources](https://md.research.elamur.ai/free/en/papers/lv-2024-full-parameter-fine-tuning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Lv, Yuqing Yang, Tengxiao Liu, et al.*2024 · 143 citations*
125. **[Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?](https://md.research.elamur.ai/free/en/papers/ravichander-2021-probing-probing-paradigm-does-probing/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Abhilasha Ravichander, Yonatan Belinkov, Eduard Hovy*2021 · 141 citations*
126. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models arXiv:2212.08037**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
127. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
128. [**The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations**Lasha Abzianidze, Johannes Bjerva, Kilian Evang, et al.*2017 · 134 citations*](https://md.research.elamur.ai/free/en/papers/abzianidze-2017-parallel-meaning-bank-multilingual-corpus/)
129. **[AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning](https://md.research.elamur.ai/free/en/papers/wang-2022-adamix-mixture-adaptations-parameter-efficient/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.*2022 · 132 citations*
130. **[FLUTE: Figurative Language Understanding through Textual Explanations](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.*2022 · 132 citations*
131. **[UnNatural Language Inference](https://md.research.elamur.ai/free/en/papers/sinha-2021-unnatural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.*2021 · 132 citations*
132. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
133. [**An Analysis of Natural Language Inference Benchmarks through the Lens of Negation**Md Mosharaf Hossain, Venelin Kovatchev, Pranoy Dutta, et al.*2020 · 130 citations*](https://md.research.elamur.ai/free/en/papers/hossain-2020-analysis-natural-language-inference-benchmarks/)
134. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models arXiv:2308.08493**Shahriar Golchin, Mihai Surdeanu*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/)
135. [**EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference**Abhilasha Ravichander, Aakanksha Naik, Carolyn Rose, et al.*2019 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ravichander-2019-equate-benchmark-evaluation-framework-quantitative/)
136. **[ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/asai-2022-attempt-parameter-efficient-multi-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.*2022 · 121 citations*
137. **[Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-don-t-take-premise-granted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.*2019 · 121 citations*
138. **[I-BERT: Integer-only BERT Quantization](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 120 citations*
139. [**Pretraining Language Models with Human Preferences arXiv:2302.08582**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
140. **[Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations](https://md.research.elamur.ai/free/en/papers/yoo-2022-ground-truth-labels-matter-deeper/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.*2022 · 113 citations*
141. [**Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework**Aaron Steven White, Pushpendre Rastogi, Kevin Duh, et al.*2017 · 110 citations*](https://md.research.elamur.ai/free/en/papers/white-2017-inference-is-everything-recasting-semantic/)
142. **[WiCE: Real-World Entailment for Claims in Wikipedia](https://md.research.elamur.ai/free/en/papers/kamoi-2023-wice-real-world-entailment-claims/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryo Kamoi, Tanya Goyal, Juan Diego Rodriguez, et al.*2023 · 109 citations*
143. **[“Ask Not What Textual Entailment Can Do for You...”](https://md.research.elamur.ai/free/en/papers/sammons-2010-ask-not-what-textual-entailment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mark Sammons, V.G.Vinod Vydiswaran, Dan Roth*2010 · 108 citations*
144. **[End-to-End Bias Mitigation by Modelling Biases in Corpora](https://md.research.elamur.ai/free/en/papers/mahabadi-2020-end-end-bias-mitigation-modelling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson*2020 · 107 citations*
145. **[Uncertain Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2020-uncertain-natural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongfei Chen, Zhengping Jiang, Adam Poliak, et al.*2020 · 103 citations*
146. **[Parallel Context Windows for Large Language Models](https://md.research.elamur.ai/free/en/papers/ratner-2023-parallel-context-windows-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nir Ratner, Yoav Levine, Yonatan Belinkov, et al.*2023 · 102 citations*
147. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
148. **[I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling](https://md.research.elamur.ai/free/en/papers/nie-2021-i-like-fish-especially-dolphins/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Nie, Mary Williamson, Mohit Bansal, et al.*2021 · 101 citations*
149. **[Understanding by Understanding Not: Modeling Negation in Language Models](https://md.research.elamur.ai/free/en/papers/hosseini-2021-understanding-understanding-not-modeling-negation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, et al.*2021 · 98 citations*
150. **[First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT](https://md.research.elamur.ai/free/en/papers/muller-2021-first-align-then-predict-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Benjamin Muller, Yanai Elazar, Benoît Sagot, et al.*2021 · 87 citations*
151. [**Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to Questions**Michael Heilman, Noah A. Smith*2010 · 86 citations*](https://md.research.elamur.ai/free/en/papers/heilman-2010-tree-edit-models-recognizing-textual/)
152. **[A Context-Theoretic Framework for Compositionality in Distributional Semantics](https://md.research.elamur.ai/free/en/papers/clarke-2012-context-theoretic-framework-compositionality-distributional/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Daoud Clarke*2012 · 84 citations*
153. **[Mitigating Label Biases for In-context Learning](https://md.research.elamur.ai/free/en/papers/fei-2023-mitigating-label-biases-context-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yifan Hou, Zeming Chen, et al.*2023 · 79 citations*
154. **[Generating Entailment Rules from FrameNet](https://md.research.elamur.ai/free/en/papers/aharon-2010-generating-entailment-rules-framenet/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roni Ben Aharon, Idan Szpektor, Ido Dagan*2010 · 71 citations*
155. **[Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue](https://md.research.elamur.ai/free/en/papers/gu-2024-model-editing-harms-general-abilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, et al.*2024 · 66 citations*
156. **[Figurative Language in Recognizing Textual Entailment](https://md.research.elamur.ai/free/en/papers/chakrabarty-2021-figurative-language-recognizing-textual-entailment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tuhin Chakrabarty, Debanjan Ghosh, Adam Poliak, et al.*2021 · 63 citations*
157. [**How well do NLI models capture verb veridicality?**Alexis Ross, Ellie Pavlick*2019 · 61 citations*](https://md.research.elamur.ai/free/en/papers/ross-2019-how-well-do-nli-models/)
158. [**Temporal Reasoning in Natural Language Inference**Siddharth Vashishtha, Adam Poliak, Yash Kumar Lal, et al.*2020 · 57 citations*](https://md.research.elamur.ai/free/en/papers/vashishtha-2020-temporal-reasoning-natural-language-inference/)
159. **[SciNLI: A Corpus for Natural Language Inference on Scientific Text](https://md.research.elamur.ai/free/en/papers/sadat-2022-scinli-corpus-natural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mobashir Sadat, Cornelia Caragea*2022 · 43 citations*
160. **[Syntactic/Semantic Structures for Textual Entailment Recognition](https://md.research.elamur.ai/free/en/papers/mehdad-2010-syntactic-semantic-structures-textual-entailment/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yashar Mehdad, Alessandro Moschitti, Fabio Massimo Zanzotto*2010 · 43 citations*
161. [**NOPE: A Corpus of Naturally-Occurring Presuppositions in English**Alicia Parrish, Sebastian Schuster, Alex Warstadt, et al.*2021 · 40 citations*](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/)
162. **[Identifying inherent disagreement in natural language inference](https://md.research.elamur.ai/free/en/papers/zhang-2021-identifying-inherent-disagreement-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xinliang Frederick Zhang, Marie-Catherine de Marneffe*2021 · 38 citations*
163. **[An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-empirical-study-model-agnostic-debiasing/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Tianyu Liu, Xin Zheng, Xiaoan Ding, et al.*2020 · 36 citations*
164. **[FATE: a FrameNet-Annotated Corpus for Textual Entailment](https://md.research.elamur.ai/free/en/papers/burchardt-2008-fate-framenet-annotated-corpus-textual/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aljoscha Burchardt, Marco Pennacchiotti*2008 · 35 citations*
165. **[BIUTEE: A Modular Open-Source System for Recognizing Textual Entailment](https://md.research.elamur.ai/free/en/papers/stern-2012-biutee-modular-open-source-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Asher Stern, Ido Dagan*2012 · 31 citations*
166. **[Integrating WordNet and FrameNet using a Knowledge-based Word Sense Disambiguation Algorithm](https://md.research.elamur.ai/free/en/papers/laparra-2009-integrating-wordnet-framenet-knowledge-based/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Egoitz Laparra, German Rigau*2009 · 30 citations*
167. **[HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-hyponli-exploring-artificial-patterns-hypothesis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tianyu Liu, Xin Zheng, Baobao Chang, et al.*2020 · 27 citations*
168. **[New Protocols and Negative Results for Textual Entailment Data Collection](https://md.research.elamur.ai/free/en/papers/bowman-2020-new-protocols-negative-results-textual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.*2020 · 27 citations*
169. **[Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation](https://md.research.elamur.ai/free/en/papers/truong-2022-not-another-negation-benchmark-nan/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Hung Thinh Truong, Yulia Otmakhova, Timothy Baldwin, et al.*2022 · 24 citations*
170. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/)
171. **[New Features for FrameNet - WordNet Mapping](https://md.research.elamur.ai/free/en/papers/tonelli-2009-new-features-framenet-wordnet-mapping/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Sara Tonelli, Daniele Pighin*2009 · 24 citations*
172. **[Getting Reliable Annotations for Sarcasm in Online Dialogues](https://md.research.elamur.ai/free/en/papers/swanson-2014-getting-reliable-annotations-sarcasm-online/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Reid Swanson, Stephanie Lukin, Luke Eisenberg, et al.*2014 · 23 citations*
173. [**Learning Scalar Adjective Intensity from Paraphrases**Anne Cocos, Skyler Wharton, Ellie Pavlick, et al.*2018 · 21 citations*](https://md.research.elamur.ai/free/en/papers/cocos-2018-learning-scalar-adjective-intensity-paraphrases/)
174. **[Is there a place for logic in recognizing textual entailment](https://md.research.elamur.ai/free/en/papers/bos-2014-is-there-place-logic-recognizing/) [Linguistic Issues in Language Technology](https://md.research.elamur.ai/free/en/venues/lilt/)**Johan Bos*2014 · 18 citations*
175. **[Partial-input baselines show that NLI models can ignore context, but they don't.](https://md.research.elamur.ai/free/en/papers/srikanth-2022-partial-input-baselines-show-that/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Neha Srikanth, Rachel Rudinger*2022 · 13 citations*
176. [**Non-entailed subsequences as a challenge for natural language inference arXiv:1811.12112**R. Thomas McCoy, Tal Linzen*2018 · 13 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2018-non-entailed-subsequences-challenge-natural/)
177. **[eXtended WordFrameNet](https://md.research.elamur.ai/free/en/papers/laparra-2010-extended-wordframenet/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Egoitz Laparra, German Rigau*2010 · 13 citations*
178. **[Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences](https://md.research.elamur.ai/free/en/papers/kabbara-2022-investigating-performance-transformer-based-nli/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jad Kabbara, Jackie Chi Kit Cheung*2022 · 12 citations*
179. [**Multi-word expressions in textual inference: Much ado about nothing?**Marie-Catherine de Marneffe, Sebastian Padó, Christopher D. Manning*2009 · 12 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2009-multi-word-expressions-textual-inference/)
180. **[How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?](https://md.research.elamur.ai/free/en/papers/srikanth-2024-how-often-are-errors-natural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Neha Srikanth, Marine Carpuat, Rachel Rudinger*2024 · 10 citations*
181. **[How Fast can BERT Learn Simple Natural Language Inference?](https://md.research.elamur.ai/free/en/papers/lin-2021-how-fast-can-bert-learn/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yi-Chung Lin, Keh-Yih Su*2021 · 10 citations*
182. **[Recognizing Textual Entailment Using Probabilistic Inference](https://md.research.elamur.ai/free/en/papers/sha-2015-recognizing-textual-entailment-probabilistic-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lei Sha, Sujian Li, Baobao Chang, et al.*2015 · 10 citations*
183. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
184. [**Automatic Identification of Infrequent Word Senses**Diana McCarthy, Rob Koeling, Julie Weeds, et al.*2004 · 9 citations*](https://md.research.elamur.ai/free/en/papers/mccarthy-2004-automatic-identification-infrequent-word-senses/)
185. **[Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences](https://md.research.elamur.ai/free/en/papers/luo-2022-simple-but-challenging-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Luo, Wei Liu, Jieyu Lin, et al.*2022 · 7 citations*
186. **[Recognizing Textual Entailment in Twitter Using Word Embeddings](https://md.research.elamur.ai/free/en/papers/sulea-2017-recognizing-textual-entailment-twitter-word/) [Workshop on Evaluating Vector Space Representations for NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-evaluating-vector-space-representations-for-nlp/)**Octavia-Maria Şulea*2017 · 7 citations*
187. **[Semantic Annotation of Textual Entailment](https://md.research.elamur.ai/free/en/papers/toledo-2013-semantic-annotation-textual-entailment/) [International Conference on Computational Semantics – Long Papers](https://md.research.elamur.ai/free/en/venues/international-conference-on-computational-semantics-long-papers/)**Assaf Toledo, Stavroula Alexandropoulou, Sophia Katrenko, et al.*2013 · 7 citations*
188. **[Labeled Alignment for Recognizing Textual Entailment](https://md.research.elamur.ai/free/en/papers/wang-2013-labeled-alignment-recognizing-textual-entailment/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Xiaolin Wang, Hai Zhao, Bao-Liang Lu*2013 · 6 citations*
189. [**English Out-of-Vocabulary Lexical Evaluation Task arXiv:1804.04242**Han Wang, Ye Wang, Xinxiang Zhang, et al.*2018 · 3 citations*](https://md.research.elamur.ai/free/en/papers/wang-2018-english-out-vocabulary-lexical-evaluation/)
190. **[Corpora for Learning the Mutual Relationship between Semantic Relatedness and Textual Entailment](https://md.research.elamur.ai/free/en/papers/vo-2016-corpora-learning-mutual-relationship-between/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ngoc Phuoc An Vo, Octavian Popescu*2016 · 3 citations*
191. **[Towards a Semantic Model for Textual Entailment Annotation](https://md.research.elamur.ai/free/en/papers/toledo-2014-semantic-model-textual-entailment-annotation/) [Linguistic Issues in Language Technology](https://md.research.elamur.ai/free/en/venues/lilt/)**Assaf Toledo, Stavroula Alexandropoulou, Sophie Chesney, et al.*2014 · 2 citations*
192. [**LCHAIM - Investigating Long Context Reasoning in Hebrew**Ehud Malul, Oriel Perets, Ziv Mor, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/malul-2025-lchaim-investigating-long-context-reasoning/)
193. **[Advancing the Arabic WordNet: Elevating Content Quality](https://md.research.elamur.ai/free/en/papers/freihat-2024-advancing-arabic-wordnet-elevating-content/) [Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT) with Shared Tasks on Arabic LLMs Hallucination and Dialect to MSA Machine Translation @ LREC-COLING](https://md.research.elamur.ai/free/en/venues/osact/)**Abed Alhakim Freihat, Hadi Mahmoud Khalilia, Gábor Bella, et al.*2024 · 1 citation*
194. **[Exploiting Open IE for Deriving Multiple Premises Entailment Corpus](https://md.research.elamur.ai/free/en/papers/vita-2019-exploiting-open-ie-deriving-multiple/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Martin Víta, Jakub Klímek*2019 · 1 citation*
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196. [**E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding arXiv:2609.33530**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral/)
197. **[NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/westhelle-2026-negnli-br-brazilian-portuguese-benchmark/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Matheus Westhelle, Viviane Moreira*2026*
198. **[Paraphrasing as Zero-shot Translation with Feature-guided Diversity Enhancement](https://md.research.elamur.ai/free/en/papers/yan-2026-paraphrasing-as-zero-shot-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyue Yan, Hongying Zan, Xinglin Lyu, et al.*2026*
199. [**Human Temporal Inferences Go Beyond Aspectual Class**Katarzyna Pruś, Mark Steedman, Adam Lopez*2024*](https://md.research.elamur.ai/free/en/papers/prus-2024-human-temporal-inferences-go-beyond/)
200. [**Exploring Lexical Irregularities in Hypothesis-Only Models of Natural Language Inference arXiv:2101.07397**Qingyuan Hu, Yi Zhang, Kanishka Misra, et al.*2021*](https://md.research.elamur.ai/free/en/papers/hu-2021-exploring-lexical-irregularities-hypothesis-only/)

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