Cover Image

CAMEL: Confidence-Gated Reflection for Reward Modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Zirui, Xu, Hailun, Luo, Yang, Liu, Yong, Sarkar, Kanchan, Xu, Kun, You, Yang
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FOCUS: Efficient Keyframe Selection for Long Video Understanding
by: Zhu, Zirui, et al.
Published: (2025)

Teaching LLMs to Abstain via Fine-Grained Semantic Confidence Reward
by: An, Hao, et al.
Published: (2025)

MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
by: Luo, Yang, et al.
Published: (2025)

How Does the Textual Information Affect the Retrieval of Multimodal In-Context Learning?
by: Luo, Yang, et al.
Published: (2024)

CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation
by: Cui, Guofeng, et al.
Published: (2025)

PACR: Progressively Ascending Confidence Reward for LLM Reasoning
by: Yoon, Eunseop, et al.
Published: (2025)

GRAM: A Generative Foundation Reward Model for Reward Generalization
by: Wang, Chenglong, et al.
Published: (2025)

Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning
by: Liu, Yong, et al.
Published: (2024)

ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework
by: Qin, Kai, et al.
Published: (2026)

SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
by: Xu, Tianyang, et al.
Published: (2024)

Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs
by: Liu, Chris Yuhao, et al.
Published: (2024)

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

Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
by: Yang, Rui, et al.
Published: (2024)

ConMax: Confidence-Maximizing Compression for Efficient Chain-of-Thought Reasoning
by: Hu, Minda, et al.
Published: (2026)

Knowledge Graph Error Detection with Contrastive Confidence Adaption
by: Liu, Xiangyu, et al.
Published: (2023)

Info-Coevolution: An Efficient Framework for Data Model Coevolution
by: Qin, Ziheng, et al.
Published: (2025)

Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
by: Bani-Harouni, David, et al.
Published: (2025)

MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models
by: Tang, Zecheng, et al.
Published: (2026)

DavIR: Data Selection via Implicit Reward for Large Language Models
by: Zhou, Haotian, et al.
Published: (2023)

Inference-Time Scaling for Generalist Reward Modeling
by: Liu, Zijun, et al.
Published: (2025)

RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution
by: Li, Jiahui, et al.
Published: (2024)

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
by: Ma, Zhengzhao, et al.
Published: (2026)

Process-based Self-Rewarding Language Models
by: Zhang, Shimao, et al.
Published: (2025)

Reasoning Models Better Express Their Confidence
by: Yoon, Dongkeun, et al.
Published: (2025)

G-MemLLM: Gated Latent Memory Augmentation for Long-Context Reasoning in Large Language Models
by: Xu, Xun
Published: (2026)

Self-Rewarding Language Models
by: Yuan, Weizhe, et al.
Published: (2024)

InfoFlow: Reinforcing Search Agent Via Reward Density Optimization
by: Luo, Kun, et al.
Published: (2025)

Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directions
by: Acharja, Samya, et al.
Published: (2026)

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
by: Zheng, Congmin, et al.
Published: (2025)

Correct Is Not Enough: Training Reasoning Planners with Executor-Grounded Rewards
by: Han, Tianyang, et al.
Published: (2026)

ToolRM: Towards Agentic Tool-Use Reward Modeling
by: Li, Renhao, et al.
Published: (2025)

Evaluating Reward Model Generalization via Pairwise Maximum Discrepancy Competitions
by: Luo, Shunyang, et al.
Published: (2026)

VerifyBench: Benchmarking Reference-based Reward Systems for Large Language Models
by: Yan, Yuchen, et al.
Published: (2025)

Multi-Perspective Consistency Enhances Confidence Estimation in Large Language Models
by: Wang, Pei, et al.
Published: (2024)

Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
by: Peng, Hao, et al.
Published: (2025)

Skill-Conditioned Gated Self-Distillation for LLM Reasoning
by: Huang, Jiazhen, et al.
Published: (2026)

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)

Towards Understanding the Influence of Reward Margin on Preference Model Performance
by: Qin, Bowen, et al.
Published: (2024)

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning
by: Zheng, Congmin, et al.
Published: (2025)

Sensitivity Meets Sparsity: The Impact of Extremely Sparse Parameter Patterns on Theory-of-Mind of Large Language Models
by: Wu, Yuheng, et al.
Published: (2025)