activity
20242026
most citedEnhancing Code LLM Training with Programmer Attention

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2026

Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery

Yifan Zhang, Xiaohan Wang, Yueke Zhang +2

Decompilation -- recovering source code from compiled binaries -- is essential for security analysis, malware reverse engineering, and legacy software maintenance. However, existin…

cs.SE2025

CodeGrad: Integrating Multi-Step Verification with Gradient-Based LLM Refinement

Yueke Zhang, Yifan Zhang, Kevin Leach +1

While Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, they often produce solutions that lack guarantees of correctness, robustness, and e…

cs.SE20252 cited

Enhancing Code LLM Training with Programmer Attention

Yifan Zhang, Chen Huang, Zachary Karas +3

Human attention provides valuable yet underexploited signals for code LLM training, offering a perspective beyond purely machine-driven attention. Despite the complexity and cost o…

cs.SE2025

Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation

Manish Acharya, Yifan Zhang, Kevin Leach +1

Optimizing software performance through automated code refinement offers a promising avenue for enhancing execution speed and efficiency. Despite recent advancements in LLMs, a sig…

cs.CR2024

MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning

Jiliang Li, Yifan Zhang, Yu Huang +1

Recent growth and proliferation of malware have tested practitioners ability to promptly classify new samples according to malware families. In contrast to labor-intensive reverse…