Author

V. Bhat

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Preprint Aug 2026

MG-VQA: Manipulation Grounded Visual Question Answering with VLMs

Vision-language models (VLMs) have shown promising spatial reasoning capabilities from static visual inputs, where the evidence needed to answer a question is available in the provided views. However, in cluttered environments, answer-relevant evidence may be occluded rather than absent: an object may lie beneath a pil...

Vineet Bhat, Mikaela Angelina Uy, Si-Yi Chen et al. · 0 citations

Preprint Aug 2026

P ROBE : 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-ef...

Vineet Bhat, Si-Yi Chen, Alex Zook et al. · 0 citations