---
title: "Who cites INSIDE: LLMs' Internal States — 106 citing papers"
description: "106 papers of the Elamur Research library cite «INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection», found in their…"
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---
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# Who cites «INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection»

106 papers of our library cite it (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · [← back to «INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection»](https://md.research.elamur.ai/free/en/papers/chen-2024-inside-llms-internal-states-retain/)

1. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
2. [**LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations arXiv:2410.02707**Hadas Orgad, Michael Toker, Zorik Gekhman, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/orgad-2024-llms-know-more-than-they/)
3. **[SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijun Yao, Weijian Qi, Liangming Pan, et al.*2025 · 52 citations*
4. [**LLM Internal States Reveal Hallucination Risk Faced With a Query arXiv:2407.03282**Ziwei Ji, Delong Chen, Etsuko Ishii, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/ji-2024-llm-internal-states-reveal-hallucination/)
5. **[Hallucination Detection in LLMs Using Spectral Features of Attention Maps](https://md.research.elamur.ai/free/en/papers/binkowski-2025-hallucination-detection-llms-spectral-features/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jakub Binkowski, Denis Janiak, Albert Sawczyn, et al.*2025 · 18 citations*
6. **[Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-revisiting-jailbreaking-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianlong Li, Zhenghua Wang, Wenhao Liu, et al.*2025 · 17 citations*
7. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
8. **[ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-icr-probe-tracking-hidden-state/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenliang Zhang, Xinyu Hu, Huixuan Zhang, et al.*2025 · 14 citations*
9. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.*2025 · 13 citations*
10. **[A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation](https://md.research.elamur.ai/free/en/papers/hou-2025-probabilistic-framework-llm-hallucination-detection/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bairu Hou, Yang Zhang, Jacob Andreas, et al.*2025 · 12 citations*
11. **[Prompt-Guided Internal States for Hallucination Detection of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-prompt-guided-internal-states-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fujie Zhang, Peiqi Yu, Biao Yi, et al.*2025 · 12 citations*
12. **[Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs](https://md.research.elamur.ai/free/en/papers/tan-2025-too-consistent-detect-study-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hexiang Tan, Fei Sun, Sha Liu, et al.*2025 · 12 citations*
13. **[Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 11 citations*
14. **[Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations](https://md.research.elamur.ai/free/en/papers/ji-2025-calibrating-verbal-uncertainty-as-linear/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziwei Ji, Lei Yu, Yeskendir Koishekenov, et al.*2025 · 11 citations*
15. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*
16. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shiyu Ni, Keping Bi, Jiafeng Guo, et al.*2025 · 9 citations*
17. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations*
18. **[Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results](https://md.research.elamur.ai/free/en/papers/santilli-2025-revisiting-uncertainty-quantification-evaluation-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.*2025 · 6 citations*
19. **[The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs](https://md.research.elamur.ai/free/en/papers/mahmoud-2026-unintended-trade-off-ai-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Mahmoud, Ali Khalil, Thommen George Karimpanal, et al.*2026 · 2 citations*
20. **[CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG Hallucinations](https://md.research.elamur.ai/free/en/papers/shi-2026-coda-restoring-contextual-dominance-copy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**JinWei Shi, Qizhuo Xie, Qianzi Hou, et al.*2026*
21. **[Constructing a Dataset for Hallucination Detection in Japanese Summarization with Fine-grained Faithfulness Labels](https://md.research.elamur.ai/free/en/papers/tanaka-2026-constructing-dataset-hallucination-detection-japanese/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hikari Tanaka, Atsushi Keyaki, Mamoru Komachi*2026*
22. **[D²-RAG: Dual-Decision Retrieval-Augmented Generation via Multi-Dimensional Uncertainty and Utility-Aware Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-d-2-rag-dual-decision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinshuo Zhang, Xiaoding Zhou, Weiyu Zhang, et al.*2026*
23. **[FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs](https://md.research.elamur.ai/free/en/papers/sawczyn-2026-factselfcheck-fact-level-black-box/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Albert Sawczyn, Jakub Binkowski, Denis Janiak, et al.*2026*
24. **[HalluZig: Hallucination Detection using Zigzag Persistence](https://md.research.elamur.ai/free/en/papers/samaga-2026-halluzig-hallucination-detection-zigzag-persistence/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shreyas N. Samaga, Gilberto Gonzalez Arroyo, Tamal K. Dey*2026*
25. **[How Retrieved Context Shapes Internal Representations in RAG](https://md.research.elamur.ai/free/en/papers/yeh-2026-how-retrieved-context-shapes-internal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Samuel Yeh, Sharon Li*2026*
26. **[LAFaCT: Attribution-based Localization and Focused Sequential Analysis of Fact-Critical Tokens for Hallucination Detection](https://md.research.elamur.ai/free/en/papers/wang-2026-lafact-attribution-based-localization-focused/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Wang, Jiahao Li, Licheng Zhang, et al.*2026*
27. **[LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries](https://md.research.elamur.ai/free/en/papers/ren-2026-latentrefusal-latent-signal-refusal-unanswerable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuancheng Ren, Shijing Hu, Zhihui Lu, et al.*2026*
28. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026*
29. **[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*
30. **[RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-rfs-guard-detecting-reasoning-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihang Liu, Fang Zhouhua, Hui Liu, et al.*2026*
31. **[The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic Truthfulness](https://md.research.elamur.ai/free/en/papers/mao-2026-digital-dunning-kruger-effect-decoupling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueheng Mao, Min Yu, Gengwang Li, et al.*2026*
32. **[TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG](https://md.research.elamur.ai/free/en/papers/lu-2026-tpa-next-token-probability-attribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengqian Lu, Jie Lu, Anjin Liu, et al.*2026*
33. **[Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/luo-2026-two-pathways-truthfulness-intrinsic-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Luo, Guangyue Peng, Wei Li, et al.*2026*
34. **[VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation](https://md.research.elamur.ai/free/en/papers/park-2026-vauq-vision-aware-uncertainty-quantification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.*2026*

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

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