---
title: "Who cites Yixin Nie — page 2 — 888 papers of our library"
description: "888 papers of the Elamur Research library cite the works of Yixin Nie, found in their bibliographies · page 2 of 2 · 101–126; the most cited first."
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---
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# Who cites Yixin Nie

958 citations of their works from 888 papers of our library (of the 141,840 whose bibliographies we read) · 126 with a page here, the most cited first · page 2 of 2 · 101–126 · [← Yixin Nie](https://md.research.elamur.ai/free/en/authors/yixin-nie/)

[← prev](https://md.research.elamur.ai/free/en/authors/yixin-nie/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/yixin-nie/cited-by/) **2**

101. **[Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://md.research.elamur.ai/free/en/papers/huang-2020-counterfactually-augmented-snli-training-data/) [Workshop on Insights from Negative Results in NLP](https://md.research.elamur.ai/free/en/venues/insights/)**William Huang, Haokun Liu, Samuel R. Bowman*2020 · 50 citations*
102. **[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*
103. **[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*
104. [**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/)
105. **[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*
106. **[Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2022-distributed-nli-learning-predict-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiang Zhou, Yixin Nie, Mohit Bansal*2022 · 35 citations*
107. **[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*
108. **[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*
109. **[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*
110. [**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/)
111. [**He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics**Nanjiang Jiang, Marie-Catherine de Marneffe*2021 · 21 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2021-he-thinks-he-knows-better/)
112. **[Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design](https://md.research.elamur.ai/free/en/papers/pyatkin-2023-design-choices-crowdsourcing-implicit-discourse/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, et al.*2023 · 19 citations*
113. **[Robustifying Multi-hop QA through Pseudo-Evidentiality Training](https://md.research.elamur.ai/free/en/papers/lee-2021-robustifying-multi-hop-qa-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kyungjae Lee, Seung-won Hwang, Sang-eun Han, et al.*2021 · 19 citations*
114. [**Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling**Stefan Grünewald, Prisca Piccirilli, Annemarie Friedrich*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/grunewald-2021-coordinate-constructions-english-enhanced-universal/)
115. **[Capture Human Disagreement Distributions by Calibrated Networks for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/wang-2022-capture-human-disagreement-distributions-calibrated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Minghan Wang, Yimeng Chen, et al.*2022 · 15 citations*
116. [**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/)
117. **[Integrating Transformers and Knowledge Graphs for Twitter Stance Detection](https://md.research.elamur.ai/free/en/papers/clark-2021-integrating-transformers-knowledge-graphs-twitter/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Thomas Clark, Costanza Conforti, Fangyu Liu, et al.*2021 · 14 citations*
118. **[Coreference Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/wu-2021-coreference-reasoning-machine-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingzhu Wu, Nafise Sadat Moosavi, Dan Roth, et al.*2021 · 11 citations*
119. **[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*
120. **[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*
121. **[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*
122. **[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*
123. **[Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization](https://md.research.elamur.ai/free/en/papers/mersinias-2022-mitigating-dataset-artifacts-natural-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Michail Mersinias, Panagiotis Valvis*2022 · 3 citations*
124. [**Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation arXiv:2604.03395**Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/alqadi-2026-arabic-benchmarks-reliable-qimma-s/)
125. **[MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility](https://md.research.elamur.ai/free/en/papers/mucha-2026-multicos-multilingual-dataset-connective-semantics/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anne Mucha, Ciyang Qing, Wataru Uegaki*2026*
126. **[Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)](https://md.research.elamur.ai/free/en/papers/liu-2024-hallucinations-large-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.*2024*

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