2 citations · 2 across the 3 of their papers we have counts for
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★ 2 cited
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…