--- title: "Who cites Dissecting Failure Dynamics in — 4 citing papers" description: "4 papers of the Elamur Research library cite «Dissecting Failure Dynamics in Large Language Model Reasoning», found in their…" canonical: "https://research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Dissecting Failure Dynamics in Large Language…](https://md.research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/) / cited by # Who cites «Dissecting Failure Dynamics in Large Language Model Reasoning» 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 «Dissecting Failure Dynamics in Large Language Model Reasoning»](https://md.research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/) 1. **[AttnPO: Attention-Guided Process Supervision for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/nie-2026-attnpo-attention-guided-process-supervision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaiyi Nie, Dingsiyu, Wenyuan Zhang, et al.*2026 · 18 citations* 2. **[Understanding LLM Reasoning for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/yuan-2026-understanding-llm-reasoning-abstractive-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haohan Yuan, Haopeng Zhang*2026 · 11 citations* 2 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/) — Dissecting Failure Dynamics in Large Language Model Reasoning