TAGGRAPH: Tag-Augmented Graphs for Graph Retrieval of Agent Persistent Histories
Long-term memory lets LLM agents recall past interactions and remain consistent across sessions, but memory systems are hard to compare because they often vary in representation, indexing, retrieval, and evaluation. We present a controlled evaluation framework based on shared 5W-style conversational memories. Localized graph configurations traverse a common base graph; AdaptiveGraph adds chronological edges and Personalized PageRank diffusion. We also evaluate BM25 over the same extracted notes and OpenClaw as a raw-input external reference. Retrieval rankings vary across memory settings. On LongMemEval-S, AdaptiveGraph is the strongest graph configuration at 0.844 MRR, but BM25 reaches 0...
| Authors | Yu-Shu Chen, Yu-Jung Liang, Pengtao Xie |
|---|---|
| Primary category | cs.IR |
| Published | 29 September 2026 |
| Last updated at source | 1 October 2026 |
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