---
title: "Who cites Towards Fully Exploiting LLM — 6 citing papers"
description: "6 papers of the Elamur Research library cite «Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception»…"
canonical: "https://research.elamur.ai/free/en/papers/ni-2025-fully-exploiting-llm-internal-states/cited-by/"
---
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# Who cites «Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception»

6 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 «Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception»](https://md.research.elamur.ai/free/en/papers/ni-2025-fully-exploiting-llm-internal-states/)

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. **[How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality](https://md.research.elamur.ai/free/en/papers/tu-2026-how-long-reasoning-chains-influence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzhu Tu, Shiyu Ni, Keping Bi*2026 · 3 citations*
3. **[Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments](https://md.research.elamur.ai/free/en/papers/mi-2026-logical-consistency-as-bridge-improving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Mi, Qiang Sheng, Shaofei Wang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/ni-2025-fully-exploiting-llm-internal-states/) — Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception