--- title: "Who cites CODERL+: Improving Code — 4 citing papers" description: "4 papers of the Elamur Research library cite «CODERL+: Improving Code Generation via Reinforcement with Execution Semantics…" canonical: "https://research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CODERL+: Improving Code Generation via…](https://md.research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/) / cited by # Who cites «CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment» 4 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «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/) 1. **[RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization](https://md.research.elamur.ai/free/en/papers/dong-2026-rl-plus-countering-capability-boundary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihong Dong, Xue Jiang, Yongding Tao, et al.*2026 · 6 citations* 2. **[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* 2 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/) — CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment