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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
GAM: Hierarchical Graph-based Agentic Memory for LLM Agents
Zhaofen Wu, Hanrong Zhang, Fulin Lin +9
To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current uni…
cs.AI2026
AgentSelect: Benchmark for Narrative Query-to-Agent Recommendation
Yunxiao Shi, Wujiang Xu, Tingwei Chen +7
LLM agents are rapidly becoming the practical interface for task automation, yet the ecosystem lacks a principled way to choose among an exploding space of deployable configuration…