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Who cites Guohao Dai

41 citations of their works from 41 papers of our library (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← Guohao Dai

  1. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 400 citations
  2. Qwen2.5-1M Technical ReportarXiv:2501.15383An Yang, Bowen Yu, Chengyuan Li, et al.2025 · 102 citations
  3. LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chi Han, Qifan Wang, Hao Peng, et al.2024 · 95 citations
  4. InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language ModelsarXiv:2503.06692Yuchen Yan, Yongliang Shen, Yang Liu, et al.2025 · 29 citations
  5. Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by TencentarXiv:2411.02265Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.2024 · 25 citations
  6. Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language ModelsInternational Conference on Computational Linguistics (COLING)Mingyang Song, Mao Zheng, Xuan Luo2025 · 20 citations
  7. LoGU: Long-form Generation with Uncertainty ExpressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruihan Yang, Caiqi Zhang, Zhisong Zhang, et al.2025 · 13 citations
  8. Evaluating Multilingual Long-Context Models for Retrieval and ReasoningWorkshop on Multilingual Representation LearningAmeeta Agrawal, Andy Dang, Sina Bagheri Nezhad, et al.2024 · 13 citations
  9. From 128K to 4M: Efficient Training of Ultra-Long Context Large Language ModelsFindings of the Association for Computational LinguisticsChejian Xu, Wei Ping, Peng Xu, et al.2026 · 5 citations
  10. Data Foundations of Long-Context Language Models: A SurveyTransactions of the Association for Computational Linguistics (TACL)Zechen Sun, Yuyang Sun, Zhaochen Su, et al.2026
  11. RoBSA: RoPE-based Blockwise Sparse Multi-head Latent AttentionAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyu Shi, Kairong Luo, Zhen Zheng, et al.2026

30 more citing papers of our library have no page here yet.

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