AI RESEARCH
MM-Conv: A Multimodal Dataset and Benchmark for Context-Aware Grounding in 3D Dialogue
arXiv CS.CL
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ArXi:2605.21796v1 Announce Type: cross Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision-language models (VLMs) excel at static image tasks, they struggle to resolve ambiguous expressions in spontaneous, multi-turn dialogue. We address this gap by