This paper turns an AI agent’s memory from a flat list of notes into a logic map of events connected by cause-and-time links.
This paper teaches a computer agent to grow a toolbox of skills that are real, runnable programs, not just text ideas.
This paper presents BEDA, a simple way to make chatty AI act strategically by turning what it believes into gentle rules (probabilistic constraints) that guide what it can say.
Youtu-Agent is a build-and-grow factory for AI agents that cuts manual setup and keeps agents improving over time.
GenEnv is a training system where a student AI and a teacher simulator grow together by exchanging tasks and feedback.
This paper builds InternGeometry, a large language model agent that solves Olympiad-level geometry by talking to a math engine, remembering what worked, and trying smart new ideas.