Paper

  • Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation

    Trevor Darrell, Lisa Dunlap, Joseph Gonzalez, Alyssa Umino, Jiezhi Yang, Han Zhang p79024-79034 from Advances in Neural Information Processing Systems 36
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  • Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement

    Daesol Cho, H. Jin Kim, Seungjae Lee p53593-53623 from Advances in Neural Information Processing Systems 36
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  • Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec

    Jun-Hyuk Kim, Seungeon Kim, Won-Hee Lee, Dokwan Oh p45956-45974 from Advances in Neural Information Processing Systems 37
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  • Diversifying Spatial-Temporal Perception for Video Domain Generalization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversifying Spatial-Temporal Perception for Video Domain Generalization

    Jia-Run Du, Yipeng Gao, Kun-Yu Lin, Wei-Shi Zheng, Jiaming Zhou p56012-56026 from Advances in Neural Information Processing Systems 36
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  • Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners

    Rujikorn Charakorn, Nat Dilokthanakul, Poramate Manoonpong p56401-56423 from Advances in Neural Information Processing Systems 37
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  • Diversity Vs. Recognizability: Human-Like Generalization in One-Shot Generative Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversity Vs. Recognizability: Human-Like Generalization in One-Shot Generative Models

    Victor Boutin, Thomas Serre, Lakshya Singhal, Xavier Thomas p20933-20946 from Advances in Neural Information Processing Systems 35
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  • Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment

    Jiawei Du, Juncheng Hu, Wenxing Huang, Xin Zhang, Joey Zhou p119443-119465 from Advances in Neural Information Processing Systems 37
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  • Divert More Attention to Vision-Language Tracking

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divert More Attention to Vision-Language Tracking

    Heng Fan, Mingzhe Guo, Liping Jing, Zhipeng Zhang p4446-4460 from Advances in Neural Information Processing Systems 35
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  • Divide and Contrast: Source-Free Domain Adaptation Via Adaptive Contrastive Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide and Contrast: Source-Free Domain Adaptation Via Adaptive Contrastive Learning

    Weikai Chen, Hui Cheng, Zhen Li, Guanbin Li, Siyuan Li, Liang Lin, Ziyi Zhang p5137-5149 from Advances in Neural Information Processing Systems 35
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  • Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback

    Jaskirat Singh, Liang Zheng p70799-70811 from Advances in Neural Information Processing Systems 36
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  • Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation

    Jingchang Chen, Qianglong Chen, Zheng Chu, Ming Liu, Bing Qin, Hongxuan Tang, Zekun Wang p67061-67105 from Advances in Neural Information Processing Systems 37
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  • Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors

    Alain Durmus, Yazid Janati, Badr Moufad, Eric Moulines, Jimmy Olsson p97408-97444 from Advances in Neural Information Processing Systems 37
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