Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching 事件

Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching arXiv:2606.03577v1 Announce Type: new Abstract: Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making it a challenging testbed for spatial reasoning in multimodal large language models (MLLMs) deployed in physical environments. However, current MLLMs lack systematic evaluation and training frameworks for these capabilities.