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请输入英文单字，中文词皆可：

upholsterer    
n. 装饰业者;家具商

装饰业者;家具商

upholsterer
n 1: a craftsman who upholsters furniture

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  • Attend Before Attention: Efficient and Scalable Video Understanding via . . .
    Trained with next-token prediction and reinforcement learning, AutoGaze autoregressively selects a minimal set of multi-scale patches that can reconstruct the video within a user-specified error threshold, eliminating redundancy while preserving information
  • Attend Before Attention: Efficient and Scalable Video Understanding via . . .
    Trained with next-token prediction and reinforcement learning, AutoGaze autoregressively selects a minimal set of multi-scale patches that can reconstruct the video within a user-specified error threshold, eliminating redundancy while preserving information
  • AutoGaze
    We propose HLVid, the first long-form, high-resolution video QA benchmark featuring 300 QA pairs on 5-minute, 4K-resolution videos Each question is manually reviewed to ensure high resolution and understanding throughout the entire video is required
  • Attend Before Attention: Efficient and Scalable Video Understanding via . . .
    AutoGaze is a lightweight module that reduces redundant video patches before processing by vision transformers or multi-modal large language models, enabling efficient processing of long, high-resolution videos while maintaining performance
  • Attend Before Attention: Efficient and Scalable Video Understanding via . . .
    Trained with next-token prediction and reinforcement learning, AutoGaze autoregressively selects a minimal set of multi-scale patches that can reconstruct the video within a user-specified error threshold, eliminating redundancy while preserving information
  • Attend Before Attention: Efficient and Scalable Video Understanding via . . .
    Abstract Multi-modal large language models (MLLMs) have advanced general-purpose video understanding but struggle with long, high-resolution videos -- they process every pixel equally in their vision transformers (ViTs) or LLMs despite significant spatiotemporal redundancy We introduce AutoGaze, a lightweight module that removes redundant patches before processed by a ViT or an MLLM Trained
  • Attend Before Attention: Efficient and Scalable Video . . .
    AutoGaze is a lightweight module that significantly enhances the efficiency of multi-modal large language models in processing long, high-resolution videos by autoregressively selecting informative patches, achieving up to 100× token reduction and 19× acceleration in processing speeds
  • nktkt paper-2026-03-25-attend-before-attention-efficient-and-scalable-vid
    Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing Baifeng Shi, Stephanie Fu, Long Lian, Hanrong Ye, David Eigen, Aaron Reite, Boyi Li, Jan Kautz, Song Han, David M Chan, Pavlo Molchanov, Trevor Darrell, Hongxu Yin UC Berkeley, MIT, Clarifai, NVIDIA arXiv: 2603 12254 (2026)





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