---
title: "Who cites LLM-Assisted Code Cleaning For — 12 citing papers"
description: "12 papers of the Elamur Research library cite «LLM-Assisted Code Cleaning For Training Accurate Code Generators», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [LLM-Assisted Code Cleaning For Training Accurate…](https://md.research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/) / cited by

# Who cites «LLM-Assisted Code Cleaning For Training Accurate Code Generators»

12 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «LLM-Assisted Code Cleaning For Training Accurate Code Generators»](https://md.research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/)

1. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
2. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
3. [**OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data arXiv:2410.01560**Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/toshniwal-2024-openmathinstruct-2-accelerating-ai-math/)
4. [**The Limits of Inference Scaling Through Resampling arXiv:2411.17501**Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/stroebl-2024-limits-inference-scaling-through-resampling/)
5. [**Rewriting Pre-Training Data Boosts LLM Performance in Math and Code arXiv:2505.02881**Kazuki Fujii, Yukito Tajima, Sakae Mizuki, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2025-rewriting-pre-training-data-boosts/)
6. **[From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/) [IEEE/ACM International Conference on Software Engineering (ICSE)](https://md.research.elamur.ai/free/en/venues/ieee-acm-international-conference-on-software-engineering-icse/)**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations*

6 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/) — LLM-Assisted Code Cleaning For Training Accurate Code Generators