Mitigating LLM Hallucination via Behaviorally Calibrated Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Jiayun, Liu, Jiashuo, Zeng, Zhiyuan, Zhan, Tianyang, Cai, Tianle, Huang, Wenhao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics
by: Liu, Jiashuo, et al.
Published: (2025)
by: Liu, Jiashuo, et al.
Published: (2025)
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
by: Wu, Jiayun, et al.
Published: (2024)
by: Wu, Jiayun, et al.
Published: (2024)
TabularMath: Evaluating Computational Extrapolation in Tabular Learning via Program-Verified Synthesis
by: Cheng, Zerui, et al.
Published: (2026)
by: Cheng, Zerui, et al.
Published: (2026)
KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning
by: Gao, Cheng, et al.
Published: (2026)
by: Gao, Cheng, et al.
Published: (2026)
Mitigating LLM Hallucinations via Conformal Abstention
by: Yadkori, Yasin Abbasi, et al.
Published: (2024)
by: Yadkori, Yasin Abbasi, et al.
Published: (2024)
Identify, Isolate, and Purge: Mitigating Hallucinations in LVLMs via Self-Evolving Distillation
by: Li, Wenhao, et al.
Published: (2025)
by: Li, Wenhao, et al.
Published: (2025)
Data Heterogeneity Modeling for Trustworthy Machine Learning
by: Liu, Jiashuo, et al.
Published: (2025)
by: Liu, Jiashuo, et al.
Published: (2025)
Towards Mitigation of Hallucination for LLM-empowered Agents: Progressive Generalization Bound Exploration and Watchdog Monitor
by: Liu, Siyuan, et al.
Published: (2025)
by: Liu, Siyuan, et al.
Published: (2025)
On Mitigating Code LLM Hallucinations with API Documentation
by: Jain, Nihal, et al.
Published: (2024)
by: Jain, Nihal, et al.
Published: (2024)
LLM Embeddings Improve Test-time Adaptation to Tabular $Y|X$-Shifts
by: Zeng, Yibo, et al.
Published: (2024)
by: Zeng, Yibo, et al.
Published: (2024)
Diagnosing Training Inference Mismatch in LLM Reinforcement Learning
by: Zhong, Tianle, et al.
Published: (2026)
by: Zhong, Tianle, et al.
Published: (2026)
Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO
by: Zeng, Zhiyuan, et al.
Published: (2026)
by: Zeng, Zhiyuan, et al.
Published: (2026)
RLoop: An Self-Improving Framework for Reinforcement Learning with Iterative Policy Initialization
by: Zhiyuan, Zeng, et al.
Published: (2025)
by: Zhiyuan, Zeng, et al.
Published: (2025)
Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
by: Liu, Zifan, et al.
Published: (2024)
by: Liu, Zifan, et al.
Published: (2024)
Transform then Explore: a Simple and Effective Technique for Exploratory Combinatorial Optimization with Reinforcement Learning
by: Pu, Tianle, et al.
Published: (2024)
by: Pu, Tianle, et al.
Published: (2024)
SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training
by: He, Zhongyu, et al.
Published: (2026)
by: He, Zhongyu, et al.
Published: (2026)
Distillation Traps and Guards: A Calibration Knob for LLM Distillability
by: Zhan, Weixiao, et al.
Published: (2026)
by: Zhan, Weixiao, et al.
Published: (2026)
Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models
by: Aminmansour, Farzane, et al.
Published: (2020)
by: Aminmansour, Farzane, et al.
Published: (2020)
Capturing LLM Capabilities via Evidence-Calibrated Query Clustering
by: Wu, Fangzhou, et al.
Published: (2026)
by: Wu, Fangzhou, et al.
Published: (2026)
Provable Reward-Agnostic Preference-Based Reinforcement Learning
by: Zhan, Wenhao, et al.
Published: (2023)
by: Zhan, Wenhao, et al.
Published: (2023)
FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction
by: Zeng, Zhiyuan, et al.
Published: (2025)
by: Zeng, Zhiyuan, et al.
Published: (2025)
Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
by: Deng, Wenhao, et al.
Published: (2025)
by: Deng, Wenhao, et al.
Published: (2025)
Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint
by: Liu, Zhihao, et al.
Published: (2025)
by: Liu, Zhihao, et al.
Published: (2025)
APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents
by: Li, Yibo, et al.
Published: (2026)
by: Li, Yibo, et al.
Published: (2026)
Revis: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
by: Wu, Jialin, et al.
Published: (2026)
by: Wu, Jialin, et al.
Published: (2026)
Mixture-of-Experts Meets In-Context Reinforcement Learning
by: Wu, Wenhao, et al.
Published: (2025)
by: Wu, Wenhao, et al.
Published: (2025)
Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
by: Luu, Tung M., et al.
Published: (2024)
by: Luu, Tung M., et al.
Published: (2024)
FAQ: Mitigating Quantization Error via Regenerating Calibration Data with Family-Aware Quantization
by: Xiao, Haiyang, et al.
Published: (2026)
by: Xiao, Haiyang, et al.
Published: (2026)
Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
by: Liang, Zhenwen, et al.
Published: (2025)
by: Liang, Zhenwen, et al.
Published: (2025)
MiMu: Mitigating Multiple Shortcut Learning Behavior of Transformers
by: Zhao, Lili, et al.
Published: (2025)
by: Zhao, Lili, et al.
Published: (2025)
Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
by: Zeng, Zhiyuan, et al.
Published: (2024)
by: Zeng, Zhiyuan, et al.
Published: (2024)
Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations
by: Hu, Wentao, et al.
Published: (2026)
by: Hu, Wentao, et al.
Published: (2026)
Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning
by: Tan, Zelin, et al.
Published: (2025)
by: Tan, Zelin, et al.
Published: (2025)
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
by: Chen, Shiqi, et al.
Published: (2024)
by: Chen, Shiqi, et al.
Published: (2024)
CARE-RL: Capability-Aware Reinforcement Learning for Mitigating Cross-Domain Conflicts
by: Zhang, Rui, et al.
Published: (2026)
by: Zhang, Rui, et al.
Published: (2026)
Mitigating Overthinking in Large Reasoning Models via Difficulty-aware Reinforcement Learning
by: Wan, Qian, et al.
Published: (2026)
by: Wan, Qian, et al.
Published: (2026)
Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
by: Zhang, Tianle, et al.
Published: (2024)
by: Zhang, Tianle, et al.
Published: (2024)
Cog-Rethinker: Hierarchical Metacognitive Reinforcement Learning for LLM Reasoning
by: Sun, Zexu, et al.
Published: (2025)
by: Sun, Zexu, et al.
Published: (2025)
Mitigating Hallucinations in Large Language Models via Causal Reasoning
by: Li, Yuangang, et al.
Published: (2025)
by: Li, Yuangang, et al.
Published: (2025)
PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representations
by: Zhu, Yinghao, et al.
Published: (2023)
by: Zhu, Yinghao, et al.
Published: (2023)
Similar Items
-
LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics
by: Liu, Jiashuo, et al.
Published: (2025) -
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
by: Wu, Jiayun, et al.
Published: (2024) -
TabularMath: Evaluating Computational Extrapolation in Tabular Learning via Program-Verified Synthesis
by: Cheng, Zerui, et al.
Published: (2026) -
KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning
by: Gao, Cheng, et al.
Published: (2026) -
Mitigating LLM Hallucinations via Conformal Abstention
by: Yadkori, Yasin Abbasi, et al.
Published: (2024)