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memory-augmented agents

topic1 events
papersTODAY 04:00 UTC

Semantic-TVM: Trustworthy Virtual Memory for Memory-Augmented AI Agents

A new arXiv paper proposes Semantic-TVM, a virtual memory design that keeps sensitive values protected while still letting agent workflows run on remote language models. The approach targets memory-augmented and tool-using agents, where retrieved memories, tool calls, and intermediate observations can leak private data. It aims to move past one-way masking, which hides values but also blocks the trusted execution they are needed for.

agents/privacy/memory/arxiv