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Research direction

Human-like Agents via Memory

Exploring how persistent and selective memory can support personalized, behaviorally consistent LLM agents.

LLM AgentsLong-term MemoryPersonalization

Overview

This project studies memory as an active component of agent behavior rather than a passive transcript store. The goal is to understand when information should be retained, revised, retrieved, or forgotten.

Motivation

Long-running agents need to preserve useful context while adapting to new evidence. A practical memory system must balance continuity with correction and avoid turning every prior interaction into permanent state.

Method

The current design space includes structured memory records, selective retrieval, update policies, and evaluation of persona and behavioral consistency across extended interaction histories.

Experiments and results

This is an active research direction. Evaluation protocols and results will be added when they are ready for public release.