🧑‍🔬 Who cites Yutaro Yamada

129 citations of their works from 129 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← Yutaro Yamada

1. ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual LearningFindings of the Association for Computational LinguisticsViet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.2023 · 422 citations
2. 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
3. Towards Building Multilingual Language Model for MedicineNature CommunicationsPengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.2024 · 184 citations
4. Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 174 citations
5. GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.2023 · 110 citations
6. Augmented Large Language Models with Parametric Knowledge GuidingarXiv:2305.04757Ziyang Luo, Can Xu, Pu Zhao, et al.2023 · 32 citations
7. Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
8. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
9. Benchmarking LLaMA-3 on Arabic Language Generation TasksArabic Natural Language Processing Conference (ArabicNLP)Md Tawkat Islam Khondaker, Numaan Naeem, Fatimah Khan, et al.2024 · 12 citations
10. EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific DiscoveryarXiv:2603.08127Yougang Lyu, Xi Zhang, Xinhao Yi, et al.2026 · 10 citations
11. AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model DiscoveryarXiv:2604.05550Yu Li, Chenyang Shao, Xinyang Liu, et al.2026 · 5 citations
12. Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response AssistanceAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Ma, Chang Guo, Zhiheng Tian, et al.2026 · 5 citations
13. AiraXiv: An AI-Driven Open-Access Platform for Human and AI ScientistsAnnual Meeting of the Association for Computational Linguistics (ACL)Junshu Pan, Panzhong Lu, Yixuan Weng, et al.2026 · 1 citation
14. ClinDet-Bench: Beyond Abstention, Evaluating Judgment Determinability of LLMs in Clinical Decision-MakingAnnual Meeting of the Association for Computational Linguistics (ACL)Yusuke Watanabe, Yohei Kobashi, Takeshi Kojima, et al.2026 · 1 citation
15. Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent CollaborationAnnual Meeting of the Association for Computational Linguistics (ACL)Zijun Liu, Zhennan Wan, Peng Li, et al.2026 · 1 citation
16. FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in LeanAnnual Meeting of the Association for Computational Linguistics (ACL)Jordan Meadows, Lan Zhang, Andre Freitas2026
17. From Guidelines to Guarantees: A Graph-Based Evaluation Harness for Domain-Specific Evaluation of LLMsWorkshop on Evaluating Evaluations (EvalEval)Jessica M. Lundin, Usman Nasir Nakakana, Guillaume Chabot-Couture2026
18. J-ClinicalBench: A Benchmark for Evaluating Large Language Models on Practical Clinical Tasks in JapaneseLanguage Resources and Evaluation Conference (LREC)Seiji Shimizu, Tomohiro Nishiyama, HISADA Shohei, et al.2026
19. Pushing the Frontiers of Scientific Fact-Checking: The SCINLP DatasetFindings of the Association for Computational LinguisticsIffat Maab, Junichi Yamagishi2026
20. Sentiment Analysis and Language Models for KwanyamaLanguage Resources and Evaluation Conference (LREC)Ndapa Nakashole2026
21. Teaching Language Models to Forecast Research Success Through Comparative Idea EvaluationFindings of the Association for Computational LinguisticsSrujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan2026

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