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cs.CL2026
Where Does the Answer Come From? Benchmarking View-Level Visual Evidence Identification in Multi-View MLLMs for Autonomous Driving
Yimu Wang, Yee Man Choi, Barry Zhang +3
Multimodal large language models (MLLMs) achieve strong results on visual reasoning benchmarks, but answer accuracy alone does not indicate whether a model relied on the correct vi…
cs.CV2026
VISTAQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence
Mozhgan Nasr Azadani, Yimu Wang, Yongpeng Zhu +5
Establishing a clear link between model predictions and the visual evidence that supports them is critical for transparency and reliability in multimodal reasoning, yet current mul…