RoboMME-Interference: Benchmarking Robot Memory Under Interference
Quick summary
arXiv:2606.22338v2 Announce Type: replace-cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment. The robot's tasks may often require it to remember information from multiple sessions ago, making long-context robot memory important for real-world deployments. However, most robot-memory benchmarks today are based on single episodes or a short context. To measure how current robot memory systems perform on longer sessions with more distractions, we introduce RoboMME-Interference, a cross-session benchmark built on Rob
Key takeaways
- arXiv:2606.22338v2 Announce Type: replace-cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment.
- The robot's tasks may often require it to remember information from multiple sessions ago, making long-context robot memory important for real-world deployments.
- However, most robot-memory benchmarks today are based on single episodes or a short context.
Why it matters
“RoboMME-Interference: Benchmarking Robot Memory Under Interference” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.