Reasoning-Guided Part-Level Visual Grounding via Reinforcement Learning

Multimodal large language models (MLLMs) ground wholeobjects well from free-form language queries, but they struggle whenthe query names a part rather than the object. We trace this to amissing object-part hierarchy, since parts are localized in the same sin-gle step used for objects. We propose Object-Part Hierarchical Reflec-tive Grounding (OP-HRG), a coarse-to-fine reasoning-guided groundingstrategy that first localizes the parent object and then the part within it.A self-check then reflects on the result, with an extension to re-encodethe predicted crop to inspect the region it is correcting. We introducea part-aware GRPO framework to train our pipeline with stage-wise re-wards. A 4B model trained this way outperforms 7B grounding LLMs andSAM3 across PascalPart, PartImageNet, and InstructPart, and transfersto reasoning segmentation. 1