--- title: "Who cites ICE-Score: Instructing Large — 30 citing papers" description: "30 papers of the Elamur Research library cite «ICE-Score: Instructing Large Language Models to Evaluate Code», found in their…" canonical: "https://research.elamur.ai/free/en/papers/zhuo-2023-ice-score-instructing-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhuo-2023-ice-score-instructing-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ICE-Score: Instructing Large Language Models to…](https://md.research.elamur.ai/free/en/papers/zhuo-2023-ice-score-instructing-large-language/) / cited by # Who cites «ICE-Score: Instructing Large Language Models to Evaluate Code» 30 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «ICE-Score: Instructing Large Language Models to Evaluate Code»](https://md.research.elamur.ai/free/en/papers/zhuo-2023-ice-score-instructing-large-language/) 1. **[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* 2. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/) 3. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/) 4. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) 5. **[Leveraging Large Language Models for NLG Evaluation: Advances and Challenges](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Li, Xiaohan Xu, Tao Shen, et al.*2024 · 63 citations* 6. [**Agent-as-a-Judge: Evaluate Agents with Agents arXiv:2410.10934**Mingchen Zhuge, Changsheng Zhao, Dylan Ashley, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/zhuge-2024-agent-judge-evaluate-agents/) 7. **[BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2023-biocoder-benchmark-bioinformatics-code-generation/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Xiangru Tang, Bill Qian, Rick Gao, et al.*2023 · 38 citations* 8. [**LLM-Assisted Code Cleaning For Training Accurate Code Generators arXiv:2311.14904**Naman Jain, Tianjun Zhang, Wei-Lin Chiang, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/) 9. **[CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks](https://md.research.elamur.ai/free/en/papers/jiang-2026-codejudgebench-benchmarking-llm-as-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongchao Jiang, Yiming Chen, Yushi Cao, et al.*2026 · 13 citations* 10. **[Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation](https://md.research.elamur.ai/free/en/papers/moon-2026-don-t-judge-code-its/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiwon Moon, Yerin Hwang, Dongryeol Lee, et al.*2026 · 5 citations* 11. **[From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-conversation-evaluation-benchmarking-llms-development/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Zhang, Lianghong Guo, Yanlin Wang, et al.*2026* 12. **[LLMs are Brittle to Simple Code Transformations: Introducing CETBench – A Benchmark for Code-Equivalence Checking](https://md.research.elamur.ai/free/en/papers/oza-2026-llms-are-brittle-simple-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Neeva Oza, Ishaan Govil, Parul Gupta, et al.*2026* 18 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhuo-2023-ice-score-instructing-large-language/) — ICE-Score: Instructing Large Language Models to Evaluate Code