--- title: "Who cites Reasoning Models Know When — 52 citing papers" description: "52 papers of the Elamur Research library cite «Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification»…" canonical: "https://research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reasoning Models Know When They're Right: Probing…](https://md.research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/) / cited by # Who cites «Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification» 52 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification»](https://md.research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/) 1. [**Dynamic Early Exit in Reasoning Models arXiv:2504.15895**Chenxu Yang, Qingyi Si, Yongjie Duan, et al.*2025 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-dynamic-early-exit-reasoning-models/) 2. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations* 3. **[Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering](https://md.research.elamur.ai/free/en/papers/jurayj-2025-is-that-your-final-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Jurayj, Jeffrey Cheng, Benjamin Van Durme*2025 · 11 citations* 4. [**What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT arXiv:2509.19284**Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-characterizes-effective-reasoning-revisiting-length/) 5. **[Confidence Should Be Calibrated More Than One Turn Deep](https://md.research.elamur.ai/free/en/papers/zhang-2026-confidence-should-be-calibrated-more/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Chengzhengxu Li, Xiaoming Liu, et al.*2026 · 3 citations* 6. **[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* 7. **[LLM Reasoning as Trajectories: Step-Specific Representation Geometry and Correctness Signals](https://md.research.elamur.ai/free/en/papers/sun-2026-llm-reasoning-as-trajectories-step/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lihao Sun, Hang Dong, Bo Qiao, et al.*2026 · 2 citations* 8. **[Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-think-how-think-mitigating-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongjiang Liu, Haoxi Li, Xiaosong Ma, et al.*2026 · 2 citations* 9. **[NEAT: Neuron-Based Early Exit for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-neat-neuron-based-early-exit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Liu, YongKang Liu, Xiaocui Yang, et al.*2026 · 1 citation* 10. **[Prior Beliefs Prejudice LLM-as-Judge: Evidence from Persuasion Evaluation](https://md.research.elamur.ai/free/en/papers/zahraei-2026-prior-beliefs-prejudice-llm-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pardis Sadat Zahraei, Xiaoning Wang, Nimet Beyza Bozdag, et al.*2026 · 1 citation* 11. **[Streaming Hallucination Detection in Long Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2026-streaming-hallucination-detection-long-chain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haolang Lu, Minghui Pan, Ripeng LI, et al.*2026 · 1 citation* 12. **[When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/xiang-2026-when-is-thinking-enough-early/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xiang, Yixin Ji, Ruotao Xu, et al.*2026 · 1 citation* 13. **[BubbleRAG: Interactive Cognitive Offloading with Thought Bubble in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-bubblerag-interactive-cognitive-offloading-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuda Ye, Jiachuan Wang, Yongqi Zhang, et al.*2026* 14. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026* 15. **[Confidence Leaps in LLM Reasoning: Early Stopping and Cross-Model Transfer](https://md.research.elamur.ai/free/en/papers/tikhonov-2026-confidence-leaps-llm-reasoning-early/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pavel Tikhonov, Ivan Oseledets, Elena Tutubalina*2026* 16. **[EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeom-2026-epicar-knowing-what-you-don/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.*2026* 17. **[Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework](https://md.research.elamur.ai/free/en/papers/zhang-2026-less-languages-less-tokens-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyuan Zhang, Qiguang Chen, Xie Chen, et al.*2026* 18. **[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* 19. **[Think Faster Than Words: Efficient LLM Chain-of-Thought Reasoning via Dynamic Shortcut Decoding](https://md.research.elamur.ai/free/en/papers/liu-2026-think-faster-than-words-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fan Liu, Yanhao Wang, Min Zhang, et al.*2026* 33 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/) — Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification