A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.
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VLMs recover reliable population-level trends in climate change visual discourse on social media even when per-image accuracy is only moderate.
A semi-supervised pipeline applies UniMatch V2 to the WeatherProof dataset by treating degraded images as unlabeled data plus test-time augmentation for semantic segmentation in adverse weather.
citing papers explorer
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Rectified Flow: A Marginal Preserving Approach to Optimal Transport
A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.
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From Codebooks to VLMs: Evaluating Automated Visual Discourse Analysis for Climate Change on Social Media
VLMs recover reliable population-level trends in climate change visual discourse on social media even when per-image accuracy is only moderate.
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A Robust Semantic Segmentation Pipeline for the CVPR 2026 8th UG2+ Challenge Track 2
A semi-supervised pipeline applies UniMatch V2 to the WeatherProof dataset by treating degraded images as unlabeled data plus test-time augmentation for semantic segmentation in adverse weather.