Cover Image

Incentivizing LLMs to Self-Verify Their Answers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Fuxiang, Xu, Jiacheng, Wang, Chaojie, Cui, Ce, Liu, Yang, An, Bo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Divide-Verify-Refine: Can LLMs Self-Align with Complex Instructions?
by: Zhang, Xianren, et al.
Published: (2024)

From Solving to Verifying: A Unified Objective for Robust Reasoning in LLMs
by: Wang, Xiaoxuan, et al.
Published: (2025)

Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
by: Liu, Chris Yuhao, et al.
Published: (2025)

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning
by: Liu, Wei, et al.
Published: (2025)

Skywork Open Reasoner 1 Technical Report
by: He, Jujie, et al.
Published: (2025)

SelfReflect: Can LLMs Communicate Their Internal Answer Distribution?
by: Kirchhof, Michael, et al.
Published: (2025)

From Stochastic Answers to Verifiable Reasoning: Interpretable Decision-Making with LLM-Generated Code
by: Mahesh, Anirudh Jaidev, et al.
Published: (2026)

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems
by: Feng, Lang, et al.
Published: (2026)

Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training
by: Liu, Yixin, et al.
Published: (2026)

Beyond the Answer: Decoding the Behavior of LLMs as Scientific Reasoners
by: Pandey, Rohan, et al.
Published: (2026)

Reasoned Safety Alignment: Ensuring Jailbreak Defense via Answer-Then-Check
by: Cao, Chentao, et al.
Published: (2025)

Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward
by: Wen, Xuexiang, et al.
Published: (2026)

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
by: Wang, Haozhe, et al.
Published: (2025)

Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers
by: Cai, Xin-Qiang, et al.
Published: (2025)

TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
by: Wei, Zhepei, et al.
Published: (2025)

Incentivizing Consistent, Effective and Scalable Reasoning Capability in Audio LLMs via Reasoning Process Rewards
by: Fan, Jiajun, et al.
Published: (2025)

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
by: DeepSeek-AI, et al.
Published: (2025)

Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning
by: Wu, Yicong, et al.
Published: (2025)

LLMs Gaming Verifiers: RLVR can Lead to Reward Hacking
by: Helff, Lukas, et al.
Published: (2026)

Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
by: Cen, Shicong, et al.
Published: (2024)

Theoretical Modeling of Large Language Model Self-Improvement Training Dynamics Through Solver-Verifier Gap
by: Sun, Yifan, et al.
Published: (2025)

One-Way Policy Optimization for Self-Evolving LLMs
by: Yang, Shuo, et al.
Published: (2026)

Heterogeneous Self-Play for Realistic Highway Traffic Simulation
by: Qiu, Jinkai, et al.
Published: (2026)

Tensor Polynomial Additive Model
by: Chen, Yang, et al.
Published: (2024)

Hindsight Hint Distillation: Scaffolded Reasoning for SWE Agents from CoT-free Answers
by: Wang, Shengjie, et al.
Published: (2026)

RLPR: Extrapolating RLVR to General Domains without Verifiers
by: Yu, Tianyu, et al.
Published: (2025)

Towards Fine-Grained and Verifiable Concept Bottleneck Models
by: Fang, Yingying, et al.
Published: (2026)

vTune: Verifiable Fine-Tuning for LLMs Through Backdooring
by: Zhang, Eva, et al.
Published: (2024)

Breaking the Safety-Capability Tradeoff: Reinforcement Learning with Verifiable Rewards Maintains Safety Guardrails in LLMs
by: Cho, Dongkyu Derek, et al.
Published: (2025)

Incentivized Lipschitz Bandits
by: Chakraborty, Sourav, et al.
Published: (2025)

Disentangling Policy from Offline Task Representation Learning via Adversarial Data Augmentation
by: Jia, Chengxing, et al.
Published: (2024)

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)

Disentangled Generative Graph Representation Learning
by: Hu, Xinyue, et al.
Published: (2024)

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
by: Wang, Peiyi, et al.
Published: (2023)

SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning
by: Liu, Bo, et al.
Published: (2025)

SCI-Verifier: Scientific Verifier with Thinking
by: Zheng, Shenghe, et al.
Published: (2025)

World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
by: Liu, Yuejiang, et al.
Published: (2026)

ANCORA: Learning to Question via Manifold-Anchored Self-Play for Verifiable Reasoning
by: Yang, Chengcao
Published: (2026)

Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning
by: Yu, Zhiyin, et al.
Published: (2026)

Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
by: Dong, Zihan, et al.
Published: (2026)