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.CV2026
GPA: Learning GUI Process Automation from Demonstrations
Zirui Zhao, Jun Hao Liew, Yan Yang +5
GUI Process Automation (GPA) is a lightweight but general vision-based Robotic Process Automation (RPA), which enables fast and stable process replay with only a single demo. Addre…
cs.AI2025
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Ziyang Luo, Zhiqi Shen, Wenzhuo Yang +7
The Model Context Protocol has emerged as a transformative standard for connecting large language models to external data sources and tools, rapidly gaining adoption across major A…