Stashbird: Efficient Speaker-Indexed Memory for Conversational Agents
- 类型：arxiv
- 标识：2609.34242
- 链接：http://arxiv.org/abs/2609.34242v1
- 主分类：agent
- 形态：method
- TLDR：AI agents require memory that preserves information across user-agent exchanges, user-to-user conversations, and group conversations with or without agent participation, while supporting updates as evidence changes or is removed. We present Stashbird, an agent memory system that links source episodes to derived memory state through explicit provenance. Stashbird organizes memory into episodic records, semantic relations, community summaries, and persisted graph state, with lifecycle operations for incremental updates and episode-level deletion. We evaluate question-answering accuracy and model
- 待LLM分类：否
- 来源文件：
- /inbox/tom/_candidates/2026-09-29-agent-rag-longcontext-candidates.json