🧑‍🔬 Who cites Koji Mineshima

188 citations of their works from 144 papers of our library (of the 141,840 whose bibliographies we read) · 23 with a page here, the most cited first · ← Koji Mineshima

1. CLUE: A Chinese Language Understanding Evaluation BenchmarkarXiv:2004.05986Liang Xu, Hai Hu, Xuanwei Zhang, et al.2020 · 243 citations
   Syntactic Data Augmentation Increases Robustness to Inference HeuristicsAnnual Meeting of the Association for Computational Linguistics (ACL)Junghyun Min, R. Thomas McCoy, Dipanjan Das, et al.2020 · 217 citations
2. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 215 citations
3. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
4. Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionPaloma Jeretic, Alex Warstadt, Suvrat Bhooshan, et al.2020 · 161 citations
5. OCNLI: Original Chinese Natural Language InferencearXiv:2010.05444Hai Hu, Kyle Richardson, Liang Xu, et al.2020 · 147 citations
6. Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language CapabilitiesarXiv:2404.17790Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.2024 · 114 citations
7. Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and NegationAtticus Geiger, Kyle Richardson, Christopher Potts2020 · 112 citations
   Probing Natural Language Inference Models through Semantic FragmentsProceedings of the AAAI Conference on Artificial IntelligenceKyle Richardson, Hai Hu, Lawrence S. Moss, et al.2019 · 102 citations
8. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 101 citations
   LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.2024 · 92 citations
   Frequency Effects on Syntactic Rule Learning in TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Jason Wei, Dan Garrette, Tal Linzen, et al.2021 · 91 citations
   Posing Fair Generalization Tasks for Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Atticus Geiger, Ignacio Cases, Lauri Karttunen, et al.2019 · 58 citations
   ANLIzing the Adversarial Natural Language Inference DatasetSociety for Computation in Linguistics (SCiL)Adina Williams, Tristan Thrush, Douwe Kiela2022 · 48 citations
   Exploring Transitivity in Neural NLI Models through VeridicalityConference of the European Chapter of the Association for Computational Linguistics (EACL)Hitomi Yanaka, Koji Mineshima, Kentaro Inui2021 · 27 citations
9. 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
10. Combining Event Semantics and Degree Semantics for Natural Language InferenceIzumi Haruta, Koji Mineshima, Daisuke Bekki2020 · 12 citations
    Decomposing Natural Logic Inferences for Neural NLIBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPJulia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.2022 · 8 citations
    Simple but Challenging: Natural Language Inference Models Fail on Simple SentencesFindings of the Association for Computational LinguisticsCheng Luo, Wei Liu, Jieyu Lin, et al.2022 · 7 citations
    Supporting Context Monotonicity Abstractions in Neural NLI ModelsWorkshops on Natural Logic Meets Machine Learning (NALOMA)Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.2021 · 5 citations
    BIS Reasoning 1.0: The First Large-Scale Japanese Benchmark for Belief-Inconsistent Syllogistic ReasoningLanguage Resources and Evaluation Conference (LREC)Ha Thanh Nguyen, Hideyuki Tachibana, Chaoran Liu, et al.2026 · 1 citation
    Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMsLanguage Resources and Evaluation Conference (LREC)Kei Moriyama, Takashi Kodama, Kouta Nakayama2026
    JSTS-Neg: Japanese Semantic Textual Similarity Dataset for Evaluating Negation Understanding AbilityLanguage Resources and Evaluation Conference (LREC)Reiko Yuasa, Yoshihide Kato, Shigeki Matsubara2026

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