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GeoLens outperforms traditional single-tool approaches by effectively integrating multiple visual reasoning tools, achieving superior accuracy and efficiency in complex remote sensing tasks.
Tail latency in LLM serving can be cut by up to 50% without relying on length predictions, reshaping how we optimize inference performance.
Achieve faster and more accurate remote sensing interpretation by intelligently pruning visual tokens based on task-specific semantic and geometric importance, without any training.
Brain network analysis gets a dynamic upgrade: M3D-BFS adaptively fuses multi-modal data based on individual samples, boosting performance beyond static methods.
MLLMs struggle to effectively zoom into relevant details in ultra-high-resolution remote sensing imagery, but a new staged training framework can teach them when and where to focus for substantial accuracy gains.
