Author

Kevin Leach

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Preprint Oct 2026

CogAdapt: Cognition-informed Sparse Adaptation of Code LLMs

Large language models (LLMs) have become increasingly capable of generating code. However, achieving stronger code-generation performance still often relies on costly model adaptation, i.e., fine-tuning pretrained model parameters. Prior studies have shown correspondence between human code processing and neural models'...

Yue-Ke Zhang, Zi-Han Fang, Kevin Leach et al. · 0 citations

Preprint Aug 2026

GraphAlignCoder: Aligning Program and Proof Graphs for Code Generation

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.

Yue-Ke Zhang, Zihan Fang, Kevin Leach et al. · 0 citations

Preprint Jul 2026

SCOPE: Leveraging Subgoal Critiques for Code Generation

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.

Yueke Zhang, Yifan Zhang, Zihan Fang et al. · 0 citations