9 papers
Evaluating QAOA expectation values can be as hard as counting optimal solutions
Stuart Hadfield
Evaluating expectation values is a critical task for variational quantum eigensolvers, and for parameterized quantum circuits and other quantum algorithms more generally. We consid…
SCOPE: Leveraging Subgoal Critiques for Code Generation
Yueke Zhang, Yifan Zhang, Zihan Fang +3
Code generation with large language models (LLMs) remains unreliable because generated programs can appear correct while still violating key semantic requirements in the natural la…
DPO-F+: Aligning Code Repair Feedback with Developers' Preferences
Zihan Fang, Yifan Zhang, Yueke Zhang +2
Large Language Models (LLMs) are increasingly used in software engineering tasks, especially code repair. However, developers often struggle to interpret model outputs, limiting ef…
SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair
Yifan Zhang, Jieyu Li, Kexin Pei +2
Large Language Models (LLMs) can generate plausible code patches, but plausibility is not enough for automated repair: a patch must compile, pass tests, and remove the target vulne…
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
Yifan Zhang, Chen Huang, Yueke Zhang +5
Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically salient code. We present EyeMulator, a mo…
VERITAS: Verifier-Guided Proof Search for Zero-Shot Formal Theorem Proving
Manish Acharya, Zhenyu Liao, Yueke Zhang +3
LLM-based formal provers often collapse rich verifier signals (syntax errors, type mismatches, partial goal progress) into a binary pass/fail bit. We present VERITAS, a zero-shot f…