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cs.CV2025
Benchmarking Visual LLMs Resilience to Unanswerable Questions on Visually Rich Documents
Davide Napolitano, Luca Cagliero, Fabrizio Battiloro
The evolution of Visual Large Language Models (VLLMs) has revolutionized the automatic understanding of Visually Rich Documents (VRDs), which contain both textual and visual elemen…
cs.CV2025
CLOSP: A Unified Semantic Space for SAR, MSI, and Text in Remote Sensing
Daniele Rege Cambrin, Lorenzo Vaiani, Giuseppe Gallipoli +2
Retrieving relevant imagery from vast satellite archives is crucial for applications like disaster response and long-term climate monitoring. However, most text-to-image retrieval…