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title: "Who cites Annotation Artifacts in — page 2 — 721 citing papers"
description: "721 papers of the Elamur Research library cite «Annotation Artifacts in Natural Language Inference Data», found in their bibliographies · page…"
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# Who cites «Annotation Artifacts in Natural Language Inference Data»

721 papers of our library cite it (of the 149,439 whose bibliographies we read) · 178 with a page here, the most cited first · page 2 of 2 · 101–178 · [← back to «Annotation Artifacts in Natural Language Inference Data»](https://md.research.elamur.ai/free/en/papers/gururangan-2018-annotation-artifacts-natural-language-inference/)

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101. [**Systematic Generalization: What Is Required and Can It Be Learned? arXiv:1811.12889**Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, et al.*2018 · 73 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2018-systematic-generalization-required-learned/)
102. [**"I'd rather just go to bed": Understanding Indirect Answers**Annie Louis, Dan Roth, Filip Radlinski*2020 · 72 citations*](https://md.research.elamur.ai/free/en/papers/louis-2020-i-d-rather-just-go/)
103. **[Evaluating BERT for natural language inference: A case study on the CommitmentBank](https://md.research.elamur.ai/free/en/papers/jiang-2019-evaluating-bert-natural-language-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nanjiang Jiang, Marie-Catherine de Marneffe*2019 · 72 citations*
104. **[Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training](https://md.research.elamur.ai/free/en/papers/stacey-2020-avoiding-hypothesis-only-bias-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joe Stacey, Pasquale Minervini, Haim Dubossarsky, et al.*2020 · 70 citations*
105. **[Towards Robustifying NLI Models Against Lexical Dataset Biases](https://md.research.elamur.ai/free/en/papers/zhou-2020-robustifying-nli-models-against-lexical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiang Zhou, Mohit Bansal*2020 · 70 citations*
106. **[Posing Fair Generalization Tasks for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/geiger-2019-posing-fair-generalization-tasks-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Atticus Geiger, Ignacio Cases, Lauri Karttunen, et al.*2019 · 61 citations*
107. **[What Does My QA Model Know? Devising Controlled Probes Using Expert Knowledge](https://md.research.elamur.ai/free/en/papers/richardson-2020-what-does-my-qa-model/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kyle Richardson, Ashish Sabharwal*2020 · 58 citations*
108. **[On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT](https://md.research.elamur.ai/free/en/papers/ravichander-2020-systematicity-probing-contextualized-word-representations/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Abhilasha Ravichander, Eduard Hovy, Kaheer Suleman, et al.*2020 · 55 citations*
109. **[Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?](https://md.research.elamur.ai/free/en/papers/balepur-2024-artifacts-or-abduction-how-do/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger*2024 · 52 citations*
110. **[ConjNLI: Natural Language Inference Over Conjunctive Sentences](https://md.research.elamur.ai/free/en/papers/saha-2020-conjnli-natural-language-inference-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swarnadeep Saha, Yixin Nie, Mohit Bansal*2020 · 51 citations*
111. **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations*
112. **[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*
113. **[Finding Generalizable Evidence by Learning to Convince Q&A Models](https://md.research.elamur.ai/free/en/papers/perez-2019-finding-generalizable-evidence-learning-convince/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Siddharth Karamcheti, Rob Fergus, et al.*2019 · 43 citations*
114. **[LitSearch: A Retrieval Benchmark for Scientific Literature Search](https://md.research.elamur.ai/free/en/papers/ajith-2024-litsearch-retrieval-benchmark-scientific-literature/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anirudh Ajith, Mengzhou Xia, Alexis Chevalier, et al.*2024 · 39 citations*
115. **[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 · 37 citations*
116. [**Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences arXiv:1810.13033**Atticus Geiger; Ignacio Cases; Lauri Karttunen;, Christopher Potts*2018 · 37 citations*](https://md.research.elamur.ai/free/en/papers/geiger-2018-stress-testing-neural-models-natural/)
117. **[MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain](https://md.research.elamur.ai/free/en/papers/herlihy-2021-mednli-is-not-immune-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Christine Herlihy, Rachel Rudinger*2021 · 30 citations*
118. **[Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning](https://md.research.elamur.ai/free/en/papers/weber-2023-mind-instructions-holistic-evaluation-consistency/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 29 citations*
119. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
120. **[Context Matters: A Pragmatic Study of PLMs' Negation Understanding](https://md.research.elamur.ai/free/en/papers/gubelmann-2022-context-matters-pragmatic-study-plms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Reto Gubelmann, Siegfried Handschuh*2022 · 28 citations*
121. **[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 · 28 citations*
122. [**SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference**Martin Schmitt, Hinrich Schütze*2019 · 28 citations*](https://md.research.elamur.ai/free/en/papers/schmitt-2019-sherliic-typed-event-focused-lexical/)
123. **[Exploring Transitivity in Neural NLI Models through Veridicality](https://md.research.elamur.ai/free/en/papers/yanaka-2021-exploring-transitivity-neural-nli-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hitomi Yanaka, Koji Mineshima, Kentaro Inui*2021 · 27 citations*
124. **[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*
125. **[Sensitivity as a Complexity Measure for Sequence Classification Tasks](https://md.research.elamur.ai/free/en/papers/hahn-2021-sensitivity-as-complexity-measure-sequence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Michael Hahn, Dan Jurafsky, Richard Futrell*2021 · 26 citations*
126. **[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*
127. [**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/)
128. **[Ecologically Valid Explanations for Label Variation in NLI](https://md.research.elamur.ai/free/en/papers/jiang-2023-ecologically-valid-explanations-label-variation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe*2023 · 19 citations*
129. **[Stress Test Evaluation of Transformer-based Models in Natural Language Understanding Tasks](https://md.research.elamur.ai/free/en/papers/aspillaga-2020-stress-test-evaluation-transformer-based/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Carlos Aspillaga, Andrés Carvallo, Vladimir Araujo*2020 · 17 citations*
130. **[Question-Answering in a Low-resourced Language: Benchmark Dataset and Models for Tigrinya](https://md.research.elamur.ai/free/en/papers/gaim-2023-question-answering-low-resourced-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fitsum Gaim, Wonsuk Yang, Hancheol Park, et al.*2023 · 16 citations*
131. **[When data permutations are pathological: the case of neural natural language inference](https://md.research.elamur.ai/free/en/papers/schluter-2018-when-data-permutations-are-pathological/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Natalie Schluter, Daniel Varab*2018 · 16 citations*
132. **[Understanding Figurative Meaning through Explainable Visual Entailment](https://md.research.elamur.ai/free/en/papers/saakyan-2025-understanding-figurative-meaning-through-explainable/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arkadiy Saakyan, Shreyas Kulkarni, Tuhin Chakrabarty, et al.*2025 · 15 citations*
133. **[When Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs)](https://md.research.elamur.ai/free/en/papers/gubelmann-2023-when-truth-matters-addressing-pragmatic/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Reto Gubelmann, Aikaterini-lida Kalouli, Christina Niklaus, et al.*2023 · 15 citations*
134. [**WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models arXiv:2311.15930**Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/benchekroun-2023-worldsense-synthetic-benchmark-grounded-reasoning/)
135. [**Adversarial Analysis of Natural Language Inference Systems arXiv:1912.03441**Tiffany Chien, Jugal Kalita*2019 · 15 citations*](https://md.research.elamur.ai/free/en/papers/chien-2019-adversarial-analysis-natural-language-inference/)
136. **[Curing the SICK and Other NLI Maladies](https://md.research.elamur.ai/free/en/papers/kalouli-2023-curing-sick-other-nli-maladies/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aikaterini-Lida Kalouli, Hai Hu, Alexander F. Webb, et al.*2023 · 14 citations*
137. **[Prompting for explanations improves Adversarial NLI. Is this true? \Yes\ it is \true\ because ıt weakens superficial cues\](https://md.research.elamur.ai/free/en/papers/kavumba-2023-prompting-explanations-improves-adversarial-nli/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.*2023 · 14 citations*
138. **[An Annotated Corpus of Reference Resolution for Interpreting Common Grounding](https://md.research.elamur.ai/free/en/papers/udagawa-2019-annotated-corpus-reference-resolution-interpreting/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 14 citations*
139. **[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*
140. **[Towards the Necessity for Debiasing Natural Language Inference Datasets](https://md.research.elamur.ai/free/en/papers/panenghat-2020-necessity-debiasing-natural-language-inference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mithun Paul Panenghat, Sandeep Suntwal, Faiz Rafique, et al.*2020 · 13 citations*
141. [**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/)
142. **[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*
143. **[A Generative Approach for Mitigating Structural Biases in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/asael-2022-generative-approach-mitigating-structural-biases/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Dimion Asael, Zachary Ziegler, Yonatan Belinkov*2022 · 10 citations*
144. **[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*
145. **[MSciNLI: A Diverse Benchmark for Scientific Natural Language Inference](https://md.research.elamur.ai/free/en/papers/sadat-2024-mscinli-diverse-benchmark-scientific-natural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mobashir Sadat, Cornelia Caragea*2024 · 9 citations*
146. **[PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers](https://md.research.elamur.ai/free/en/papers/saxon-2023-peco-examining-single-sentence-label/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Saxon, Xinyi Wang, Wenda Xu, et al.*2023 · 9 citations*
147. **[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*
148. [**Investigating Biases in Textual Entailment Datasets arXiv:1906.09635**Shawn Tan, Yikang Shen, Chin-wei Huang, et al.*2019 · 7 citations*](https://md.research.elamur.ai/free/en/papers/tan-2019-investigating-biases-textual-entailment-datasets/)
149. **[SSR: Utilizing Simplified Stance Reasoning Process for Robust Stance Detection](https://md.research.elamur.ai/free/en/papers/yuan-2022-ssr-utilizing-simplified-stance-reasoning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jianhua Yuan, Yanyan Zhao, Yanyue Lu, et al.*2022 · 6 citations*
150. **[Annotation Difficulties in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/kalouli-2021-annotation-difficulties-natural-language-inference/) [Brazilian Symposium in Information and Human Language Technology](https://md.research.elamur.ai/free/en/venues/stil/)**Aikaterini-Lida Kalouli, Livy Real, Annebeth Buis, et al.*2021 · 5 citations*
151. **[Evaluating Numeracy of Language Models as a Natural Language Inference Task](https://md.research.elamur.ai/free/en/papers/mahendra-2025-evaluating-numeracy-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.*2025 · 4 citations*
152. [**A guide to the dataset explosion in QA, NLI, and commonsense reasoning**Anna Rogers, Anna Rumshisky*2020 · 4 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-guide-dataset-explosion-qa-nli/)
153. **[FinNLI: Novel Dataset for Multi-Genre Financial Natural Language Inference Benchmarking](https://md.research.elamur.ai/free/en/papers/magomere-2025-finnli-novel-dataset-multi-genre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jabez Magomere, Elena Kochkina, Samuel Mensah, et al.*2025 · 3 citations*
154. **[NLI under the Microscope: What Atomic Hypothesis Decomposition Reveals](https://md.research.elamur.ai/free/en/papers/srikanth-2025-nli-under-microscope-what-atomic/) [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*2025 · 3 citations*
155. **[How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics](https://md.research.elamur.ai/free/en/papers/cosma-2024-how-hard-is-this-test/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adrian Cosma, Stefan Ruseti, Mihai Dascalu, et al.*2024 · 3 citations*
156. **[PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments](https://md.research.elamur.ai/free/en/papers/asami-2023-propres-investigating-projectivity-presupposition-various/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Daiki Asami, Saku Sugawara*2023 · 3 citations*
157. **[Improving the Precision of Natural Textual Entailment Problem Datasets](https://md.research.elamur.ai/free/en/papers/bernardy-2020-improving-precision-natural-textual-entailment/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jean-Philippe Bernardy, Stergios Chatzikyriakidis*2020 · 3 citations*
158. [**Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference arXiv:2410.08996**Grace Proebsting, Adam Poliak*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/proebsting-2024-hypothesis-only-biases-large-language/)
159. [**Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns arXiv:2201.07614**Reto Gubelmann, Siegfried Handschuh*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gubelmann-2022-uncovering-more-shallow-heuristics-probing/)
160. [**Understanding Roles and Entities: Datasets and Models for Natural Language Inference arXiv:1904.09720**Arindam Mitra, Ishan Shrivastava, Chitta Baral*2019 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2019-understanding-roles-entities-datasets-models/)
161. **[Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection](https://md.research.elamur.ai/free/en/papers/stacey-2026-improving-ood-performance-closed-source/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joe Stacey, Lisa Alazraki, Aran Ubhi, et al.*2026 · 1 citation*
162. **[SynthLLM: An LLM-based Scalable Synthetic Data Generation Pipeline for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/panahi-2026-synthllm-llm-based-scalable-synthetic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Solmaz Panahi, Vasudevan Nedumpozhimana, John Kelleher*2026 · 1 citation*
163. **[Towards a Diagnostic and Predictive Evaluation Methodology for Sequence Labeling Tasks](https://md.research.elamur.ai/free/en/papers/mellado-2026-diagnostic-predictive-evaluation-methodology-sequence/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Elena Alvarez-Mellado, Julio Gonzalo*2026 · 1 citation*
164. **[Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/proebsting-2025-biases-large-language-model-elicited/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Grace Proebsting, Adam Poliak*2025 · 1 citation*
165. **[From Form to Function: A Constructional NLI Benchmark](https://md.research.elamur.ai/free/en/papers/bonial-2025-form-function-constructional-nli-benchmark/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Claire Bonial, Taylor Pellegrin, Melissa Torgbi, et al.*2025 · 1 citation*
166. **[On Reference (In-)Determinacy in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2025-reference-determinacy-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.*2025 · 1 citation*
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