MemFuse: Multi-Source Memory Fusion from Fragmented Observations
Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on single-source textual histories. In realistic settings, however, relevant information is often fragmented across applications and devices, as well as across users and time, requiring agents to integrate dispersed observations into coherent episodic memories while preserving their source provenance. To address these gaps, we introduce **MemFuseBench**, a benchmark for *multi-source memory fusion*. MemFuseBench is built with a Scene-to-Sensor pipeline that synthesizes controllable scenarios into source-tagged observations, evidence-grounded qu...
| Authors | Chao Li, Yuanfa Li, Wenhao Wu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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