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Jevmem is an automatic project memory tool for AI coding assistants like Claude Code, Cursor, and Codex that saves decisions and constraints from chats into a markdown file for future context.
This paper introduces AdMem, a unified memory framework for LLM-based agents that integrates semantic, episodic, and procedural memory with a bi-level short-term and long-term store, using a multi-agent architecture for automatic memory generation and adaptive retrieval. Experiments show improved robustness and success on long multi-turn tasks.