---
title: "Who cites Hung Le — 190 papers of our library"
description: "190 papers of the Elamur Research library cite the works of Hung Le, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hung-le/cited-by/"
---
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# Who cites Hung Le

191 citations of their works from 190 papers of our library (of the 149,439 whose bibliographies we read) · 55 with a page here, the most cited first · [← Hung Le](https://md.research.elamur.ai/free/en/authors/hung-le/)

1. **[Reflexion: Language Agents with Verbal Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Noah Shinn, Federico Cassano, Edward Berman, et al.*2023 · 2,271 citations*
2. [**Code Llama: Open Foundation Models for Code arXiv:2308.12950**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,430 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
3. [**DAPO: An Open-Source LLM Reinforcement Learning System at Scale arXiv:2503.14476**Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.*2025 · 668 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-dapo-open-source-llm-reinforcement/)
4. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
5. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing arXiv:2305.11738**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
6. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
7. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
8. [**From System 1 to System 2: A Survey of Reasoning Large Language Models arXiv:2502.17419**Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.*2025 · 165 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-system-1-system-2-survey/)
9. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
10. **[Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*
11. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 134 citations*
12. **[OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement](https://md.research.elamur.ai/free/en/papers/zheng-2024-opencodeinterpreter-integrating-code-generation-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Zheng, Ge Zhang, Tianhao Shen, et al.*2024 · 129 citations*
13. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
14. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
15. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
16. **[MapCoder: Multi-Agent Code Generation for Competitive Problem Solving](https://md.research.elamur.ai/free/en/papers/islam-2024-mapcoder-multi-agent-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez*2024 · 118 citations*
17. **[Self-Edit: Fault-Aware Code Editor for Code Generation](https://md.research.elamur.ai/free/en/papers/zhang-2023-self-edit-fault-aware-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kechi Zhang, Zhuo Li, Jia Li, et al.*2023 · 105 citations*
18. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
19. [**Identifying the Risks of LM Agents with an LM-Emulated Sandbox arXiv:2309.15817**Yangjun Ruan, Honghua Dong, Andrew Wang, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2023-identifying-risks-lm-agents-lm/)
20. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
21. [**Planning with Large Language Models for Code Generation arXiv:2303.05510**Shun Zhang, Zhenfang Chen, Yikang Shen, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/)
22. [**Is Self-Repair a Silver Bullet for Code Generation? arXiv:2306.09896**Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2024-self-repair-silver-bullet-code/)
23. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
24. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
25. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
26. **[SelfCodeAlign: Self-Alignment for Code Generation](https://md.research.elamur.ai/free/en/papers/wei-2024-selfcodealign-self-alignment-code-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.*2024 · 32 citations*
27. [**Can Language Models Solve Olympiad Programming? arXiv:2404.10952**Quan Shi, Michael Tang, Karthik Narasimhan, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/)
28. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations*
29. **[CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-codetree-agent-guided-tree-search/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jierui Li, Hung Le, Yingbo Zhou, et al.*2025 · 21 citations*
30. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations*
31. **[MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/park-2025-maporl-multi-agent-post-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chanwoo Park, Seungju Han, Xingzhi Guo, et al.*2025 · 15 citations*
32. [**Preference Optimization for Reasoning with Pseudo Feedback arXiv:2411.16345**Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2024-preference-optimization-reasoning-pseudo-feedback/)
33. **[RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/dong-2025-rag-critic-leveraging-automated-critic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Jiajie Jin, Xiaoxi Li, et al.*2025 · 14 citations*
34. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
35. **[Problem Solving Through Human–AI Preference-based Cooperation](https://md.research.elamur.ai/free/en/papers/dutta-2025-problem-solving-through-human-ai/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.*2025 · 9 citations*
36. **[M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation](https://md.research.elamur.ai/free/en/papers/liu-2025-m2rc-eval-massively-multilingual-repository/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaheng Liu, Ken Deng, Congnan Liu, et al.*2025 · 8 citations*
37. **[CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment](https://md.research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Jiang, Yihong Dong, Mengyang Liu, et al.*2026 · 5 citations*
38. **[a1: Steep Test-time Scaling Law via Environment Augmented Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-a1-steep-test-time-scaling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 2 citations*
39. **[One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement](https://md.research.elamur.ai/free/en/papers/zhou-2026-one-refiner-unlock-them-all/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixiao Zhou, Dongzhou Cheng, Zhiliang wu, et al.*2026 · 2 citations*
40. **[Scaling Laws for Code: Every Programming Language Matters](https://md.research.elamur.ai/free/en/papers/yang-2026-scaling-laws-code-every-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Yang, Shuyue Guo, Linzheng Chai, et al.*2026 · 2 citations*
41. **[Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models](https://md.research.elamur.ai/free/en/papers/samadi-2026-scaling-test-time-compute-achieve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran, et al.*2026 · 1 citation*
42. **[SWE-Mutation: Can LLMs Generate Reliable Test Suites in Software Engineering?](https://md.research.elamur.ai/free/en/papers/sun-2026-swe-mutation-can-llms-generate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxuan Sun, Yuze Zhao, Yufeng Wang, et al.*2026 · 1 citation*
43. **[The Bidirectional Process Reward Model](https://md.research.elamur.ai/free/en/papers/zhang-2026-bidirectional-process-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingyin Zhang, Jun Gao, Xiaoxue Ren, et al.*2026 · 1 citation*
44. **[Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*
45. **[Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization](https://md.research.elamur.ai/free/en/papers/rahman-2026-aligning-text-code-vision-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mizanur Rahman, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, et al.*2026*
46. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
47. **[Bootstrapping Code Translation with Weighted Multilanguage Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-bootstrapping-code-translation-weighted-multilanguage/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhan Wu, Huan Zhang, Wei Cheng, et al.*2026*
48. **[Chronos: Learning Temporal Dynamics of Reasoning Chains for Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/zhang-2026-chronos-learning-temporal-dynamics-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Jiayi Liao, Chengpeng Li, et al.*2026*
49. **[CodeRM-NT: Reward Model for Code RL without Unit Tests](https://md.research.elamur.ai/free/en/papers/xia-2026-coderm-nt-reward-model-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xia, Dan Zhang, Tianrui Sun*2026*
50. **[CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment](https://md.research.elamur.ai/free/en/papers/shayanfar-2026-codial-interpretable-task-oriented-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Radin Shayanfar, Chu Fei Luo, Rohan V Bhambhoria, et al.*2026*
51. **[MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification Enhancement](https://md.research.elamur.ai/free/en/papers/xu-2026-mavencoder-competitive-code-generation-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZhenChun Xu, Yi Cai, Dajun Zheng, et al.*2026*
52. **[Plug-and-Play Data Module for Code RL: Adaptive Ambiguity Replay](https://md.research.elamur.ai/free/en/papers/zhang-2026-plug-play-data-module-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianqing Zhang, Wei Xia, Zhezheng Hao, et al.*2026*
53. **[SeDev: Structured Semantic Exploration for LLM-Driven Code Generation](https://md.research.elamur.ai/free/en/papers/yang-2026-sedev-structured-semantic-exploration-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ronghui Yang, Jie Liu, Jiajie Zeng, et al.*2026*
54. **[SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthfix-adaptive-neuro-symbolic-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Zhang, Jieyu Li, Kexin Pei, et al.*2026*
55. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

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