2 papers
cs.IR2026
When Memory Takes Gradients: Collaborative Vector Memory for Agentic Recommender Systems
Hanchong Chen, Xing Tang, Lingjie Li +2
Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memory is text: a narrative written…
cs.AI2026
Reading is not Reasoning: Bridging the Agentic Policy Gap in Vision-Text Compression
Cheng Fan, Junyi Zhou, Tingzhang Luo +5
Multi-step language-model agents repeatedly process growing interaction histories, leading to substantial context costs. Vision--text compression reduces these costs by rendering h…