LangPrecip treats weather text as semantic motion constraints in a rectified-flow trajectory generator to improve multimodal precipitation nowcasting, yielding over 60% and 19% gains in heavy-rain CSI at 80-minute lead times on Swedish and MRMS data.
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Presents LLaVA-AlignedVQ, an edge-cloud VQA system with AlignedVQ that delivers 1365x feature compression, 96.8% lower transmission than JPEG90, 2-15x speedup, and accuracy within -2.23% to +1.6% of the baseline across eight datasets.
LLM-PeerReview ensembles LLMs by scoring responses with LLM-as-Judge and selecting the best via averaging or truth inference, beating Smoothie-Global by 6.9-7.3 points on four datasets.
citing papers explorer
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LangPrecip: Language-Aware Multimodal Precipitation Nowcasting
LangPrecip treats weather text as semantic motion constraints in a rectified-flow trajectory generator to improve multimodal precipitation nowcasting, yielding over 60% and 19% gains in heavy-rain CSI at 80-minute lead times on Swedish and MRMS data.
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Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models
Presents LLaVA-AlignedVQ, an edge-cloud VQA system with AlignedVQ that delivers 1365x feature compression, 96.8% lower transmission than JPEG90, 2-15x speedup, and accuracy within -2.23% to +1.6% of the baseline across eight datasets.
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Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process
LLM-PeerReview ensembles LLMs by scoring responses with LLM-as-Judge and selecting the best via averaging or truth inference, beating Smoothie-Global by 6.9-7.3 points on four datasets.