2 citations · 3 across the 5 of their papers we have counts for
7 papers
EyeLayer: Integrating Human Attention Patterns into LLM-Based Code Summarization
Jiahao Zhang, Yifan Zhang, Kevin Leach +1
Code summarization is the task of generating natural language descriptions of source code, which is critical for software comprehension and maintenance. While large language models…
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…
A Human Study of Cognitive Biases in Web Application Security
Yuwei Yang, Skyler Grandel, Daniel Balasubramanian +2
Cybersecurity training has become a crucial part of computer science education and industrial onboarding. Capture the Flag (CTF) competitions have emerged as a valuable, gamified a…
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…
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…
Towards Fair Pay and Equal Work: Imposing View Time Limits in Crowdsourced Image Classification
Gordon Lim, Stefan Larson, Yu Huang +1
Crowdsourcing is a common approach to rapidly annotate large volumes of data in machine learning applications. Typically, crowd workers are compensated with a flat rate based on an…