Personalized, Aligned, Long-Term Memory for AI Systems (PALM) Workshop

Long-term memory is becoming a core capability for AI agents and AI assistants, enabling them to remember user preferences, past interactions, tool-use traces, multimodal context, and evolving task histories across sessions. Yet current research remains fragmented across agent memory, personalization, benchmarking, multimodal learning, cognitive models, privacy, and safety. The PALM workshop will bring these communities together to study persistent memory as an infrastructure layer for personalized, aligned, and long-term AI agents. The workshop will focus on memory architectures, evaluation protocols, user control, and emerging safety risks, including privacy leakage, memory poisoning, over-personalization, sycophancy, sleeper memories, and long-term behavioral manipulation. By combining invited talks, contributed papers, posters, and a panel, PALM aims to define shared research questions and safeguards for robust, user-governed memory systems.