--- title: "Who cites LoopTool: Closing the — 5 citing papers" description: "5 papers of the Elamur Research library cite «LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls», found in their…" canonical: "https://research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [LoopTool: Closing the Data–Training Loop for…](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) / cited by # Who cites «LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls» 5 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 «LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls»](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) 1. **[Rethinking Entropy Interventions in RLVR: An Entropy Change Perspective](https://md.research.elamur.ai/free/en/papers/hao-2026-rethinking-entropy-interventions-rlvr-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhezheng Hao, Hong Wang, Haoyang Liu, et al.*2026 · 22 citations* 2. **[Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors](https://md.research.elamur.ai/free/en/papers/zhang-2026-robust-tool-use-fission-grpo/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiwei Zhang, Fei Zhao, Rui Wang, et al.*2026 · 1 citation* 3 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) — LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls