Paper

  • Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach

    Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji, Dacheng Tao p30950-30962 from Advances in Neural Information Processing Systems 35
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  • Make Some Noise: Reliable and Efficient Single-Step Adversarial Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make Some Noise: Reliable and Efficient Single-Step Adversarial Training

    Pau De Jorge Aranda, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip Torr, Gregory Rogez, Puneet Dokania p12881-12893 from Advances in Neural Information Processing Systems 35
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  • Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

    Zhongqi Yue, Qianru Sun, Hanwang Zhang p26991-27004 from Advances in Neural Information Processing Systems 36
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  • Make Your LLM Fully Utilize the Context

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make Your LLM Fully Utilize the Context

    Shengnan An, Zexiong Ma, Zeqi Lin, Nanning Zheng, Jian-Guang Lou, Weizhu Chen p62160-62188 from Advances in Neural Information Processing Systems 37
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  • Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion

    Yongyuan Liang, Tingqiang Xu, Kaizhe Hu, Guangqi Jiang, Furong Huang, Huazhe Xu p19288-19306 from Advances in Neural Information Processing Systems 37
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  • Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials

    Ye Fang, Zeyi Sun, Tong Wu, Jiaqi Wang, Ziwei Liu, Gordon Wetzstein, Dahua Lin p99262-99298 from Advances in Neural Information Processing Systems 37
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  • Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels

    Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland p12542-12553 from Advances in Neural Information Processing Systems 35
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  • Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning

    Qi Wang, Junming Yang, Yunbo Wang, Xin Jin, Wenjun Zeng, Xiaokang Yang p97203-97230 from Advances in Neural Information Processing Systems 37
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  • Making Scalable Meta Learning Practical

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Making Scalable Meta Learning Practical

    Sang Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric Xing p26271-26290 from Advances in Neural Information Processing Systems 36
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  • Making Sense of Dependence: Efficient Black-Box Explanations Using Dependence Measure

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Making Sense of Dependence: Efficient Black-Box Explanations Using Dependence Measure

    Paul Novello, Thomas Fel, David Vigouroux p4344-4357 from Advances in Neural Information Processing Systems 35
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  • MALT Powers Up Adversarial Attacks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    MALT Powers Up Adversarial Attacks

    Odelia Melamed, Gilad Yehudai, Adi Shamir p44366-44392 from Advances in Neural Information Processing Systems 37
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  • MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection

    Haoyang He, Yuhu Bai, Jiangning Zhang, Qingdong He, Hongxu Chen, Zhenye Gan, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Lei Xie p71162-71187 from Advances in Neural Information Processing Systems 37
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