VLMs show a resolution illusion on UHR Earth observation imagery where higher resolution does not improve micro-target perception; UHR-Micro benchmark and MAP-Agent address this via evidence-centered active inspection.
Vision-language models for vision tasks: A survey.IEEE transactions on pattern analysis and machine intelligence, 46(8):5625–5644
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EvoIR-Agent formulates experience components into a hierarchical pool with a self-evolving update mechanism to improve performance and efficiency of training-free MLLM image restoration agents over prior paradigms.
citing papers explorer
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UHR-Micro: Diagnosing and Mitigating the Resolution Illusion in Earth Observation VLMs
VLMs show a resolution illusion on UHR Earth observation imagery where higher resolution does not improve micro-target perception; UHR-Micro benchmark and MAP-Agent address this via evidence-centered active inspection.
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EvoIR-Agent: Self-Evolving Image Restoration Agentic System via Experience-Driven Learning
EvoIR-Agent formulates experience components into a hierarchical pool with a self-evolving update mechanism to improve performance and efficiency of training-free MLLM image restoration agents over prior paradigms.