Groupwise Agentic Grading and Advantage Redistribution for Code Agent RL

arXiv:2609.32577 · cs.CL, cs.LG · Submitted 2026-09-26 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Reinforcement Learning — 12× in this paper · explained in 4 episodes
• GRPO — 6× in this paper · explained in 6 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Credit assignment — 4× in this paper · explained in 3 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Multimodal Reasoning — 2× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Reward Shaping — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Failure Modes — 1× in this paper · explained in 3 episodes
• Group Relative Policy Optimization — 1× in this paper
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Groupwise Agentic Grading for Advantage Redistribution — 1× in this paper
• Trace — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning
• SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
• DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks
• Prioritizing the Best: Incentivizing Reliable Multimodal Reasoning by Rewarding Beyond Answer Correctness
• No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping
• Leveraging Error Diversity in Group Rollouts for Reinforcement Learning
• Understanding R1-Zero-Like Training: A Critical Perspective
• Agent Lightning: Train ANY AI Agents with Reinforcement Learning
• How Much, Then Where: Credit-Conserving Action-to-Token Allocation for Multi-Turn Agent Reinforcement Learning
• HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• GTPO and GRPO-S: Token and Sequence-Level Reward Shaping with Policy Entropy
• PAPO: Stabilizing Rubric Integration Training via Decoupled Advantage Normalization
• Kimi K3: Open Frontier Intelligence
• TRIAGE: Role-Typed Credit Assignment for Agentic Reinforcement Learning
• GRRM: Group Relative Reward Modeling for Machine Translation

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