Cover Image

Reward Hacking in Rubric-Based Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mahmoud, Anas, Rezaei, MohammadHossein, Wang, Zihao, Gunjal, Anisha, Liu, Bing, He, Yunzhong
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR
by: Tyagi, Utkarsh, et al.
Published: (2026)

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
by: Gunjal, Anisha, et al.
Published: (2025)

Online Rubrics Elicitation from Pairwise Comparisons
by: Rezaei, MohammadHossein, et al.
Published: (2025)

Agentic Rubrics as Contextual Verifiers for SWE Agents
by: Raghavendra, Mohit, et al.
Published: (2026)

Chasing the Tail: Effective Rubric-based Reward Modeling for Large Language Model Post-Training
by: Zhang, Junkai, et al.
Published: (2025)

Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification
by: Gunjal, Anisha, et al.
Published: (2024)

Reinforcement Learning with Robust Rubric Rewards
by: Yu, Ya-Qi, et al.
Published: (2026)

IR$^3$: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking
by: Beigi, Mohammad, et al.
Published: (2026)

Self-Rewarding Rubric-Based Reinforcement Learning for Open-Ended Reasoning
by: Ye, Zhiling, et al.
Published: (2025)

Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models
by: Nath, Vaskar, et al.
Published: (2025)

GARDO: Reinforcing Diffusion Models without Reward Hacking
by: He, Haoran, et al.
Published: (2025)

Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking
by: Beigi, Mohammad, et al.
Published: (2026)

Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning
by: Gan, Siyuan, et al.
Published: (2026)

Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
by: Xie, Lipeng, et al.
Published: (2025)

Toward IIT-Inspired Consciousness in LLMs: A Reward-Based Learning Framework
by: Akbari, Hamid Reza, et al.
Published: (2026)

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

Visual Preference Optimization with Rubric Rewards
by: Yu, Ya-Qi, et al.
Published: (2026)

Gradient Regularization Prevents Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
by: Ackermann, Johannes, et al.
Published: (2026)

Honesty to Subterfuge: In-Context Reinforcement Learning Can Make Honest Models Reward Hack
by: McKee-Reid, Leo, et al.
Published: (2024)

AdaRubric: Task-Adaptive Rubrics for Reliable LLM Agent Evaluation and Reward Learning
by: Ding, Liang
Published: (2026)

Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort
by: Wang, Xinpeng, et al.
Published: (2025)

School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs
by: Taylor, Mia, et al.
Published: (2025)

Hack-Verifiable Environments: Towards Evaluating Reward Hacking at Scale
by: Roth, Amit, et al.
Published: (2026)

Reward Shaping to Mitigate Reward Hacking in RLHF
by: Fu, Jiayi, et al.
Published: (2025)

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)

Reinforcement Learning with Rubric Anchors
by: Huang, Zenan, et al.
Published: (2025)

Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents
by: Huang, Jiawei, et al.
Published: (2026)

Reward Hacking Mitigation using Verifiable Composite Rewards
by: Tarek, Mirza Farhan Bin, et al.
Published: (2025)

Repairing Reward Functions with Feedback to Mitigate Reward Hacking
by: Hatgis-Kessell, Stephane, et al.
Published: (2025)

ODIN: Disentangled Reward Mitigates Hacking in RLHF
by: Chen, Lichang, et al.
Published: (2024)

AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning
by: Wu, Peilin, et al.
Published: (2026)

Reward Hacking as Equilibrium under Finite Evaluation
by: Wang, Jiacheng, et al.
Published: (2026)

Rubrics to Tokens: Bridging Response-level Rubrics and Token-level Rewards in Instruction Following Tasks
by: Xu, Tianze, et al.
Published: (2026)

LLM Reasoning with Process Rewards for Outcome-Guided Steps
by: Rezaei, Mohammad, et al.
Published: (2026)

R3: Robust Rubric-Agnostic Reward Models
by: Anugraha, David, et al.
Published: (2025)

Alternating Reinforcement Learning with Contextual Rubric Rewards: Beyond the Scalarization Strategy
by: Lan, Guangchen, et al.
Published: (2026)

Reward and Guidance through Rubrics: Promoting Exploration to Improve Multi-Domain Reasoning
by: Bi, Baolong, et al.
Published: (2025)

TutorBench: A Benchmark To Assess Tutoring Capabilities Of Large Language Models
by: Srinivasa, Rakshith S, et al.
Published: (2025)

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria
by: Tian, Juanxi, et al.
Published: (2026)

EgoNormia: Benchmarking Physical Social Norm Understanding
by: Rezaei, MohammadHossein, et al.
Published: (2025)