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PMCoder is presented, an issue-resolution agent that couples a hierarchical phase planner with episodic memory that outperforms either component alone and reduces repeated failed actions, empty-patch exits, and context-window exhaustion.
GraphAlignCoder is introduced, a training framework that transfers explicit correctness structure into code generation and consistently outperforms the base model, code-only SFT, and CodeRL across all benchmarks.
SCOPE is presented, a prover-initialized subgoal critic for code generation that adapts a Lean-oriented prover model to produce three parseable feedback fields for downstream code generation: subgoals, gap analysis, and a robustness checklist.
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