MEMOBench: A Process Level Memory Benchmark for Robotic Manipulation
Robotic manipulation often requires acting on information that is no longer visible, yet Vision-Language-Action policies are usually evaluated when the current observation largely determines the next action. Existing robotic memory benchmarks expose this gap, but they still rely mainly on final task success and therefore conflate forgetting with manipulation failure. We present \textbf{MEMOBench}, a benchmark for process level memory evaluation in robotic manipulation. MEMOBench includes 30 history dependent tasks, 1{,}500 expert demonstrations, and 4{,}200 executable checkpoint instances from 84 templates. Each checkpoint pairs coarse to fine language with a simulator predicate and label...
| Authors | Haiyang Sun, Haoxiao Wang, Junming Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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