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cs.AI2026
Seeing, Maintaining, and Learning: The Evolution of Multimodal Agent Memory
Minghao Guo, Qingyue Jiao, Xiujin Liu +77
Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating information across multiple modalities…
cs.AI2026
Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory
Taeil Kim, Kangsan Kim, Sung Ju Hwang
Memory systems have shown promise for improving agent performance, but their potential remains largely unexplored for small language models, which struggle to generate sufficient s…
cs.AI2026
Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents
Kangsan Kim, Minki Kang, Taeil Kim +3
Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization to homogeneous task domains, f…