Author

Jiepan Li

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Preprint Aug 2026

DIVE: Dynamic Iterative Visual Evidence Construction for Efficient Vision-Language Models

DIVE (Dynamic Iterative Visual Evidence Construction), a training-free framework that recasts visual-token pruning as dynamic evidence construction and builds a retained set of complementary, prompt-relevant evidence.

Cheng Zhong, Xiao An, Zijie Wang et al. · 0 citations

Jul 2026

Advancing All-Weather Building Damage Mapping to the Instance Level: Outcomes and Insights from the 2026 Bright Challenge

Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, may be unavailable because of cloud, smoke, or darkness. The Bright Challenge evaluated all-weather building damage mapping from a submeter-re...

Hongruixuan Chen, He Huang, Haifeng Wang et al. · arXiv.org · 0 citations