The 2nd Workshop on Lifelong Agent: Learning, Aligning, Evolving

Artificial intelligence is entering a new phase: from one-shot assistants to persistent agents that remember, act, and adapt across extended interactions. Recent work increasingly studies agents as stateful systems with memory, planning, tool use, and environment interaction, rather than static models evaluated only on short-horizon benchmarks. This shift makes the central challenge more concrete: how can agents continuously improve while remaining reliable, efficient, and aligned over time?

The notion of a lifelong agent offers a natural lens for this challenge. A lifelong agent should not only acquire new knowledge and skills, but also manage memory, personalize safely, interact with evolving tool ecosystems, and withstand long-term deployment without drift or brittle failures. This workshop brings these emerging directions under a unified agenda centered on agents that learn, align, and evolve throughout their lifespan.

As the second edition of the Lifelong Agents workshop, this event builds on the strong community interest from the first edition while moving the conversation toward next-stage questions: how learning changes alignment, how new tools alter reliability, how personalization affects oversight, and how persistent deployment demands new forms of evaluation and governance. By bringing together language agents, reinforcement learning, multimodal and embodied systems, human-AI interaction, evaluation, and AI safety, we aim to shape a coherent roadmap for agents that can be built responsibly and studied rigorously under real-world conditions.