---
title: "Who cites KodCode: A Diverse, Challenging, — 27 citing papers"
description: "27 papers of the Elamur Research library cite «KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/xu-2025-kodcode-diverse-challenging-verifiable-synthetic/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [KodCode: A Diverse, Challenging, and Verifiable…](https://md.research.elamur.ai/free/en/papers/xu-2025-kodcode-diverse-challenging-verifiable-synthetic/) / cited by

# Who cites «KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding»

27 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding»](https://md.research.elamur.ai/free/en/papers/xu-2025-kodcode-diverse-challenging-verifiable-synthetic/)

1. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 347 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
2. **[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*
3. [**The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models arXiv:2505.22617**Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-entropy-mechanism-reinforcement-learning-reasoning/)
4. [**OpenCodeReasoning: Advancing Data Distillation for Competitive Coding arXiv:2504.01943**Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2025-opencodereasoning-advancing-data-distillation-competitive/)
5. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
6. **[rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset](https://md.research.elamur.ai/free/en/papers/liu-2025-rstar-coder-scaling-competitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yifei Liu, Li Lyna Zhang, Yi Zhu, et al.*2025 · 8 citations*
7. **[ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-execverify-white-box-rl-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingxiao Tang, He Ye, Zhaoyang Chu, et al.*2026 · 1 citation*
8. **[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*
9. **[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*
10. **[MTP-RL: Acceleration of Reinforcement Learning Rollouts with Policy-Aligned Multi-Token Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-mtp-rl-acceleration-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ke Wang, Aohan Zeng, Zhengxiao Du, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/xu-2025-kodcode-diverse-challenging-verifiable-synthetic/) — KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding