BoostAPR boosts automated program repair by training a sequence-level assessor and line-level credit allocator from execution outcomes, then applying them in PPO to reach 40.7% on SWE-bench Verified.
• Learning rate:1×10 −5 • Batch size: 64 • Epochs: 5 • Optimizer: AdamW (β 1 = 0.9,β 2 = 0.999) • Hybrid loss weight:λ reg = 0.5 B.3
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BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
BoostAPR boosts automated program repair by training a sequence-level assessor and line-level credit allocator from execution outcomes, then applying them in PPO to reach 40.7% on SWE-bench Verified.