Survey proposes two-axis framework for multimodal agent memory
A survey submitted to arXiv on 14 Oct 2026 (arXiv:2610.19366) by Minghao Guo and 79 co-authors reviews how multimodal agents handle memory. It organizes the field along two axes: Axis I covers how multimodal information is formed and represented (for example modality-specific embeddings, textual and structured records, latent and parametric representations), while Axis II splits memory management into T1 static memory, T2 dynamic memory and T3 self-evolving memory, describing how management policies adapt as experience accumulates. From that framework the authors synthesize recurring design patterns and principles, including balancing source fidelity against abstraction, preserving temporal validity and provenance, grounding memory use in recoverable evidence, and evolving memory policies over time, and they outline open challenges and future directions.
As multimodal agents move toward long-horizon and lifelong tasks, memory determines whether they remain coherent across sessions and adapt to changing users and environments; this framework offers a shared vocabulary for comparing approaches.