AI RESEARCH
Research on Vision-Language Question Answering Models for Industrial Robots
arXiv CS.CV
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ArXi:2605.01483v1 Announce Type: new A hierarchical cross-modal fusion model is proposed for vision-language question answering (VLQA) in industrial robotics, targeting the challenges of semantic ambiguity, complex environmental layouts, and domain-specific terminology common in modern manufacturing. The framework integrates advanced object detection, multi-scale visual encoding, syntactic parsing, and task-aware semantic attention to unite vision and language signals into a joint reasoning space.