D2-V2X: Depth-Driven Cooperative V2X Reasoning for Autonomous Driving 事件

D2-V2X: Depth-Driven Cooperative V2X Reasoning for Autonomous Driving arXiv:2605.24098v1 Announce Type: new Abstract: Single-vehicle Vision-Language Models (VLMs) are fundamentally constrained by sensor occlusions. While Vehicle-to-Everything (V2X) systems mitigate this, current benchmarks lack the cooperative reasoning required for resolving ambiguities in complex environments. We introduce D2-V2X, a spatially-aware Question-Rationale-Answer (QRA) benchmark featuring 8,500 triplets derived fro