3 papers
cs.SE2026
CodeEvolve: LLM-Driven Evolutionary Optimization with Runtime-Enriched Target Selection for Multi-Language Code Enhancement
Ajay Krishna Borra, Wenzhuo Yang, Samarth Arora +9
We present CodeEvolve, an evolutionary framework for improving program performance and code quality with Large Language Models (LLMs). CodeEvolve extends OpenEvolve with runtime-gu…
cs.SE2025
CodeTF: One-stop Transformer Library for State-of-the-art Code LLMs
Nghi D. Q. Bui, Hung Le, Yue Wang +3
Code intelligence plays a key role in transforming modern software engineering. Recently, deep learning-based models, especially Transformer-based large language models (LLMs), hav…
cs.SE2024
PerfCodeGen: Improving Performance of LLM Generated Code with Execution Feedback
Yun Peng, Akhilesh Deepak Gotmare, Michael Lyu +3
Large Language Models (LLMs) are widely adopted for assisting in software development tasks, yet their performance evaluations have narrowly focused on the functional correctness o…