🧑‍🔬 Who cites Cheng-Yu Hsieh

563 citations of their works from 560 papers of our library (of the 141,840 whose bibliographies we read) · 38 with a page here, the most cited first · ← Cheng-Yu Hsieh

1. A Survey of Large Language ModelsWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,863 citations
2. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsLonghui Yu, Weisen Jiang, Han Shi, et al.2023 · 556 citations
3. Kimi k1.5: Scaling Reinforcement Learning with LLMsKimi Team, Angang Du, Bofei Gao, et al.2025 · 413 citations
4. Query Rewriting in Retrieval-Augmented Large Language ModelsXinbei Ma, Yeyun Gong, Pengcheng He, et al.2023 · 383 citations
5. A Survey on Model Compression for Large Language ModelsXunyu Zhu, Jian Li, Yong Liu, et al.2024 · 381 citations
6. Orca: Progressive Learning from Complex Explanation Traces of GPT-4Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.2023 · 358 citations
7. On-Policy Distillation of Language Models: Learning from Self-Generated MistakesRishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.2023 · 288 citations
8. Large Language Models for Data Annotation and Synthesis: A SurveyZhen Tan, Dawei Li, Song Wang, et al.2024 · 259 citations
9. RedPajama: an Open Dataset for Training Large Language ModelsMaurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 247 citations
10. The False Promise of Imitating Proprietary LLMsArnav Gudibande, Eric Wallace, Charlie Snell, et al.2023 · 178 citations
11. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelLoubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 171 citations
12. Promptbreeder: Self-Referential Self-Improvement Via Prompt EvolutionChrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.2023 · 165 citations
13. MiniCheck: Efficient Fact-Checking of LLMs on Grounding DocumentsLiyan Tang, Philippe Laban, Greg Durrett2024 · 159 citations
14. Fanar: An Arabic-Centric Multimodal Generative AI PlatformFanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
15. OpenThoughts: Data Recipes for Reasoning ModelsEtash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 113 citations
16. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 113 citations
17. DistiLLM: Towards Streamlined Distillation for Large Language ModelsJongwoo Ko, Sungnyun Kim, Tianyi Chen, et al.2024 · 111 citations
18. Olmo 3Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 109 citations
19. TrueTeacher: Learning Factual Consistency Evaluation with Large Language ModelsZorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.2023 · 106 citations
20. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguageGuilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 97 citations
21. On Learning to Summarize with Large Language Models as ReferencesYixin Liu, Kejian Shi, Katherine He, et al.2024 · 94 citations
22. GLM-5: from Vibe Coding to Agentic EngineeringAohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 89 citations
23. Small Language Models: Survey, Measurements, and InsightsZhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
24. How to Train Long-Context Language Models (Effectively)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 84 citations
25. CODI: Compressing Chain-of-Thought into Continuous Space via Self-DistillationZhenyi Shen, Hanqi Yan, Linhai Zhang, et al.2025 · 76 citations
26. The Unreasonable Ineffectiveness of the Deeper LayersAndrey Gromov, Kushal Tirumala, Hassan Shapourian, et al.2024 · 69 citations
27. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAlejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 67 citations
28. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningMarc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
29. Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesChaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 42 citations
30. Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMsNicolas Boizard, Kevin El Haddad, Celine Hudelot, et al.2024 · 34 citations
31. Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and ParaphrasingJaehun Jung, Peter West, Liwei Jiang, et al.2023 · 34 citations
32. Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference TuningShengguang Wu, Shusheng Yang, Zhenglun Chen, et al.2024 · 16 citations
33. Arabic Stable LM: Adapting Stable LM 2 1.6B to ArabicZaid Alyafeai, Michael Pieler, Hannah Teufel, et al.2024 · 6 citations
34. Rationale-Guided Distillation for E-Commerce Relevance Classification: Bridging Large Language Models and Lightweight Cross-EncodersSanjay Agrawal, Faizan Ahemad, Vivek Varadarajan Sembium2025 · 1 citation
35. Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual DataChristian Schuler, Raman Ahmad, Ānrán Wáng, et al.2026
36. ProBel: Propaganda Detection with Techniques, Spans, and ExplanationsMohamed Bayan Kmainasi, Ali Ezzat Shahroor, Elisa Sartori, et al.2026
37. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
38. Reason-to-Learn (R2L): Multi-Agent Knowledge Distillation for Lightweight LLMs in Sentiment AnalysisLe-Huy Tu, Quan Nguyen, Vincent NGUYEN, et al.2026

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

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/cheng-yu-hsieh/cited-by/