DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory 事件

DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory arXiv:2605.15759v3 Announce Type: replace Abstract: Large language model (LLM) agents require long-term memory to leverage information from past interactions. However, existing memory systems often face a fidelity--efficiency trade-off: raw dialogue histories are expensive, while flat facts or summaries may discard the structure needed for precise recall. We propose \textbf{DimMem}, a lightweight dimensional memory framework t