SMMBench: A Benchmark for Source-Distributed Multimodal Agent Memory
Existing benchmarks for multimodal memory reasoning largely evaluate systems within pre-assembled contexts, but under-evaluate whether agents can use evidence distributed across independently originated sources. We argue that source-distributed memory composition is an important and under-examined bottleneck in multimodal agent memory, especially when relevant evidence is fragmented across heterogeneous artifacts such as conversations, profiles, screenshots, tables, images, and documents. To address this gap, we introduce Source-distributed Multimodal Memory Benchmark(SMMBench), which measures whether agents can retrieve, align, and compose multimodal evidence scattered across multiple so...
| Authors | Huacan Chai, Yukai Wang, Yingxuan Yang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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