3 papers
cs.LG2026
Understanding the Challenges in Iterative Generative Optimization with LLMs
Allen Nie, Xavier Daull, Zhiyi Kuang +10
Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using execution feedback. It is a promising approach…
cs.LG2025
Learning Game-Playing Agents with Generative Code Optimization
Zhiyi Kuang, Ryan Rong, YuCheng Yuan +1
We present a generative optimization approach for learning game-playing agents, where policies are represented as Python programs and refined using large language models (LLMs). Ou…
cs.SE2023
Challenging Bug Prediction and Repair Models with Synthetic Bugs
Ali Reza Ibrahimzada, Yang Chen, Ryan Rong +1
Bugs are essential in software engineering; many research studies in the past decades have been proposed to detect, localize, and repair bugs in software systems. Effectiveness eva…