robotics
The Robot Moved the Clutter Before It Answered
PROBE turns visual question answering into an active task where a robot must reveal occluded objects before deciding.
Summary
PROBE turns visual question answering into an active task where a robot must reveal occluded objects before deciding.
PROBE-Bench contains 150 simulated tabletop tasks across six question types, with picking and pushing tools that change the scene between observations. Agentic tool use outperformed perception-only baselines by 8.0 percent on average, and distilled open-weight agents gained another 11.5 percent over their off-the-shelf agent baselines. The authors also report real-tabletop transfer, but the benchmark remains a bounded step toward robots that can answer questions about hidden household state.
Why it matters
PROBE turns visual question answering into an active task where a robot must reveal occluded objects before deciding.
Limits and context
- Agentic tool use outperformed perception-only baselines by 8.0 percent on average, and distilled open-weight agents gained another 11.5 percent over their off-the-shelf agent baselines.
Key claims
PROBE turns visual question answering into an active task where a robot must reveal occluded objects before deciding.
Qualification: Agentic tool use outperformed perception-only baselines by 8.0 percent on average, and distilled open-weight agents gained another 11.5 percent over their off-the-shelf agent baselines.
Evidence: source-2026-08-19-015
Sources
- arXiv preprint 2608.17129arXiv · primary research
Corrections
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