---
title: "Who cites FACT-E: Causality-Inspired — 7 citing papers"
description: "7 papers of the Elamur Research library cite «FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/sun-2026-fact-e-causality-inspired-evaluation/cited-by/"
---
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# Who cites «FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning»

7 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning»](https://md.research.elamur.ai/free/en/papers/sun-2026-fact-e-causality-inspired-evaluation/)

1. **[Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-rag-mitigating-retrieval-permutation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianchi Zhang, Hainan Zhang, Liang Pang, et al.*2026 · 27 citations*
2. **[Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS](https://md.research.elamur.ai/free/en/papers/xu-2026-self-correcting-rag-enhancing-faithfulness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Zhou Wu, Xiaolong Jia, et al.*2026 · 15 citations*
3. **[GCoT-Decoding: Unlocking Deep Reasoning Paths for Universal Question Answering](https://md.research.elamur.ai/free/en/papers/luo-2026-gcot-decoding-unlocking-deep-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guanran Luo, Wentao Qiu, Zhongquan Jian, et al.*2026 · 6 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/sun-2026-fact-e-causality-inspired-evaluation/) — FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning