Menglin Xia, Xuchao Zhang, Shantanu Dixit, Paramaguru Harimurugan, Rujia Wang, Victor Ruhle, Robert Sim, Chetan Bansal, Saravan Rajmohan
Memora is a memory representation system that balances abstraction and specificity to improve retrieval relevance and reasoning effectiveness in agent memory systems.
Memora is a new approach to memory systems for AI agents, designed to handle large amounts of information efficiently. It strikes a balance between generalizing information (abstraction) and keeping detailed specifics, which is important for accurate reasoning. Memora organizes information in a way that makes it easier to find relevant details by linking related pieces of memory together. This system has been tested and shown to perform better than existing methods on specific benchmarks, meaning it can retrieve more relevant information and reason more effectively as the memory grows.
