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dacl-challenge: Semantic Segmentation during Visual Bridge Inspections., , , , , , , , and . WACV (Workshops), page 716-725. IEEE, (2024)dacl10k: Benchmark for Semantic Bridge Damage Segmentation., , and . CoRR, (2023)Probing the Role of Positional Information in Vision-Language Models., and . CoRR, (2023)Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model., , , and . CoRR, (2022)dacl1k: Real-World Bridge Damage Dataset Putting Open-Source Data to the Test., , , and . CoRR, (2023)dacl10k: Benchmark for Semantic Bridge Damage Segmentation., , and . WACV, page 8611-8620. IEEE, (2024)Probing the Role of Positional Information in Vision-Language Models., and . NAACL-HLT (Findings), page 1031-1041. Association for Computational Linguistics, (2022)Building Inspection Toolkit: Unified Evaluation and Strong Baselines for Damage Recognition., , , and . CoRR, (2022)Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples., , , and . CoRR, (2024)Building Inspection Toolkit: Unified Evaluation And Strong Baselines For Bridge Damage Recognition., , , and . ICIP, page 1221-1225. IEEE, (2022)