Image de couverture de livre

CLUE: Non-parametric Verification from Experience via Hidden-State Clustering

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Liang, Zhenwen, Li, Ruosen, Zhou, Yujun, Song, Linfeng, Yu, Dian, Du, Xinya, Mi, Haitao, Yu, Dong
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation
par: Zhou, Yujun, et autres
Publié: (2025)

Save the Good Prefix: Precise Error Penalization via Process-Supervised RL to Enhance LLM Reasoning
par: Liu, Haolin, et autres
Publié: (2026)

FG-PRM: Fine-grained Hallucination Detection and Mitigation in Language Model Mathematical Reasoning
par: Li, Ruosen, et autres
Publié: (2024)

PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
par: Li, Ruosen, et autres
Publié: (2023)

DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification
par: Liu, Rui, et autres
Publié: (2026)

SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models
par: Yu, Dian, et autres
Publié: (2024)

Stable and Efficient Single-Rollout RL for Multimodal Reasoning
par: Liu, Rui, et autres
Publié: (2025)

Verified Critical Step Optimization for LLM Agents
par: Li, Mukai, et autres
Publié: (2026)

Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values
par: Yu, Dian, et autres
Publié: (2025)

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
par: Tian, Ye, et autres
Publié: (2024)

EconProver: Towards More Economical Test-Time Scaling for Automated Theorem Proving
par: Li, Mukai, et autres
Publié: (2025)

Dual-Uncertainty Guided Policy Learning for Multimodal Reasoning
par: Liu, Rui, et autres
Publié: (2025)

IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering
par: Li, Ruosen, et autres
Publié: (2024)

Group Distributionally Robust Optimization-Driven Reinforcement Learning for LLM Reasoning
par: Panaganti, Kishan, et autres
Publié: (2026)

Teaching LLMs to Refine with Tools
par: Yu, Dian, et autres
Publié: (2024)

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
par: Dai, Runpeng, et autres
Publié: (2025)

Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning
par: Wang, Xiyao, et autres
Publié: (2024)

Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains
par: Su, Yi, et autres
Publié: (2025)

Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
par: Zhang, Yuheng, et autres
Publié: (2025)

Locas: Your Models are Principled Initializers of Locally-Supported Parametric Memories
par: Lu, Sidi, et autres
Publié: (2026)

AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
par: Li, Ruosen, et autres
Publié: (2025)

Inconsistent dialogue responses and how to recover from them
par: Zhang, Mian, et autres
Publié: (2024)

LiteSearch: Efficacious Tree Search for LLM
par: Wang, Ante, et autres
Publié: (2024)

Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration Pitfalls
par: Wang, Ante, et autres
Publié: (2025)

Guided Self-Evolving LLMs with Minimal Human Supervision
par: Yu, Wenhao, et autres
Publié: (2025)

A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
par: Li, Xiangci, et autres
Publié: (2024)

Towards Solving More Challenging IMO Problems via Decoupled Reasoning and Proving
par: Liang, Zhenwen, et autres
Publié: (2025)

Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
par: Zhang, Yuheng, et autres
Publié: (2024)

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
par: He, Zhiwei, et autres
Publié: (2025)

Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data
par: Liang, Zhenwen, et autres
Publié: (2026)

Entropy Guided Extrapolative Decoding to Improve Factuality in Large Language Models
par: Das, Souvik, et autres
Publié: (2024)

Collaborative decoding of critical tokens for boosting factuality of large language models
par: Jin, Lifeng, et autres
Publié: (2024)

DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search
par: Yue, Murong, et autres
Publié: (2024)

Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis
par: Shi, Yucheng, et autres
Publié: (2026)

R-Zero: Self-Evolving Reasoning LLM from Zero Data
par: Huang, Chengsong, et autres
Publié: (2025)

DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning
par: Zhang, Ziyin, et autres
Publié: (2025)

Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
par: Liang, Zhenwen, et autres
Publié: (2025)

MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data Curation
par: Liang, Zhenwen, et autres
Publié: (2025)

HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving
par: Li, Yang, et autres
Publié: (2024)

Scaling Synthetic Data Creation with 1,000,000,000 Personas
par: Ge, Tao, et autres
Publié: (2024)