Author

Jonathan Tremblay

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Preprint Aug 2026

PROBE: Manipulation-Grounded Visual Question Answering with VLM Agents

This work develops PROBE, a framework for benchmarking and finetuning VLM agents on cluttered tabletop scenes, and designs PROBE-Agent, a finetuning recipe to distill successful trajectories from a powerful teacher foundation model to a smaller open-weight model using a mixed data recipe that encourages manipulation-efficient question answering.

V. Bhat, Siyi Chen, Alex Zook et al. · 0 citations