Talk Title: Towards Self-Evolving Software Intelligence

Talk Abstract: In recent years, Large Language Models (LLMs) have shown impressive performance across a wide range of downstream applications, including software engineering. This talk explores the evolution and recent trends of software engineering agents, featuring our recent work on Live-SWE-agent and Self-Play SWE-RL. We will discuss how these recent efforts enable live coding LLMs and software agents capable of autonomous and continuous self-improvement, paving the way toward next-level software intelligence.

Bio: Lingming Zhang is an associate professor at University of Illinois Urbana-Champaign. His research lies at the intersection of Software Engineering and Machine Learning. His group has pioneered a series of work on LLM-based software testing, repair, and synthesis (such as TitanFuzz, AlphaRepair, and Agentless), and also released multiple open code LLMs (including the recent SWE-RL, PurpCode, and Code World Model), with millions of downloads worldwide. Their techniques for training and improving code LLMs or agents have been adopted by leading AI companies, including Meta, Google, OpenAI, MiniMax, and DeepSeek.