Cover Image

Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Anqi, Chen, Yulin, Pan, Jane, Zhao, Chen, Panda, Aurojit, Li, Jinyang, He, He
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Do Language Models Know When They're Hallucinating References?
by: Agrawal, Ayush, et al.
Published: (2023)

Draft Model Knows When to Stop: Self-Verification Speculative Decoding for Long-Form Generation
by: Zhang, Ziyin, et al.
Published: (2024)

Do Androids Know They're Only Dreaming of Electric Sheep?
by: CH-Wang, Sky, et al.
Published: (2023)

Thinking Out Loud: Do Reasoning Models Know When They're Right?
by: Zeng, Qingcheng, et al.
Published: (2025)

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?
by: Mei, Zhiting, et al.
Published: (2025)

Do Small Language Models Know When They're Wrong? Confidence-Based Cascade Scoring for Educational Assessment
by: Burleigh, Tyler
Published: (2026)

When Models Know More Than They Say: Probing Analogical Reasoning in LLMs
by: McGovern, Hope, et al.
Published: (2026)

Spontaneous Reward Hacking in Iterative Self-Refinement
by: Pan, Jane, et al.
Published: (2024)

Do LLMs Signal When They're Right? Evidence from Neuron Agreement
by: Chen, Kang, et al.
Published: (2025)

Knowing When Not to Answer: Abstention-Aware Scientific Reasoning
by: Abdaljalil, Samir, et al.
Published: (2026)

Shorten After You're Right: Lazy Length Penalties for Reasoning RL
by: Yuan, Danlong, et al.
Published: (2025)

Do Retrieval Augmented Language Models Know When They Don't Know?
by: Zhou, Youchao, et al.
Published: (2025)

Self-DC: When to Reason and When to Act? Self Divide-and-Conquer for Compositional Unknown Questions
by: Wang, Hongru, et al.
Published: (2024)

Know More, Know Clearer: A Meta-Cognitive Framework for Knowledge Augmentation in Large Language Models
by: Chen, Hao, et al.
Published: (2026)

What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say "I Don't Know"
by: Lee, Joosung, et al.
Published: (2026)

Can AI Assistants Know What They Don't Know?
by: Cheng, Qinyuan, et al.
Published: (2024)

ConfSpec: Efficient Step-Level Speculative Reasoning via Confidence-Gated Verification
by: Liu, Siran, et al.
Published: (2026)

Large Language Models Often Know When They Are Being Evaluated
by: Needham, Joe, et al.
Published: (2025)

From Reasoning to Learning: A Survey on Hypothesis Discovery and Rule Learning with Large Language Models
by: He, Kaiyu, et al.
Published: (2025)

ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs
by: Zhang, Zhenliang, et al.
Published: (2025)

Knowing You Don't Know: Learning When to Continue Search in Multi-round RAG through Self-Practicing
by: Yang, Diji, et al.
Published: (2025)

Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models
by: Furuya, Kotaro, et al.
Published: (2026)

Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
by: Liu, Xiaoyuan, et al.
Published: (2025)

Trade-offs in Large Reasoning Models: An Empirical Analysis of Deliberative and Adaptive Reasoning over Foundational Capabilities
by: Zhao, Weixiang, et al.
Published: (2025)

A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning
by: Hong, Ruixin, et al.
Published: (2023)

When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models
by: Mao, Yingzhi, et al.
Published: (2025)

Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding
by: Liu, Tianqiao, et al.
Published: (2024)

When Chain-of-Thought Fails, the Solution Hides in the Hidden States
by: Mehrafarin, Houman, et al.
Published: (2026)

KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
by: Chen, Zhuo, et al.
Published: (2025)

Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method
by: Zhao, Yukun, et al.
Published: (2023)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
by: Singhi, Nishad, et al.
Published: (2025)

SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling
by: Chen, Jiefeng, et al.
Published: (2025)

Does RAG Know When Retrieval Is Wrong? Diagnosing Context Compliance under Knowledge Conflict
by: Chen, Yihang, et al.
Published: (2026)

CaRT: Teaching LLM Agents to Know When They Know Enough
by: Liu, Grace, et al.
Published: (2025)

Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification
by: Shi, Weili, et al.
Published: (2026)

Self-Verification Dilemma: Experience-Driven Suppression of Overused Checking in LLM Reasoning
by: Long, Quanyu, et al.
Published: (2026)

Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
by: Chen, Haolin, et al.
Published: (2024)

Reasoning in Action: MCTS-Driven Knowledge Retrieval for Large Language Models
by: Liu, Shuqi, et al.
Published: (2025)

Retrieving, Rethinking and Revising: The Chain-of-Verification Can Improve Retrieval Augmented Generation
by: He, Bolei, et al.
Published: (2024)

RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement
by: Jiang, Jinhao, et al.
Published: (2024)