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

    Rongrong Ji, Peng Mi, Tianhe Ren, Li Shen, Xiaoshuai Sun, Dacheng Tao, Yiyi Zhou 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

    Adel Bibi, Pau De Jorge Aranda, Puneet Dokania, Gregory Rogez, Amartya Sanyal, Philip Torr, Riccardo Volpi 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

    Qianru Sun, Zhongqi Yue, 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, Weizhu Chen, Zeqi Lin, Jian-Guang Lou, Zexiong Ma, Nanning Zheng 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

    Kaizhe Hu, Furong Huang, Guangqi Jiang, Yongyuan Liang, Huazhe Xu, Tingqiang 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, Dahua Lin, Ziwei Liu, Zeyi Sun, Jiaqi Wang, Gordon Wetzstein, Tong Wu 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

    Wonho Bae, Mohamad Amin Mohamadi, 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

    Xin Jin, Qi Wang, Yunbo Wang, Junming Yang, Xiaokang Yang, Wenjun Zeng 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

    Hwijeen Ahn, Sang Choe, Sanket Vaibhav Mehta, Willie Neiswanger, Emma Strubell, Pengtao Xie, 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

    Thomas Fel, Paul Novello, 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, Adi Shamir, Gilad Yehudai 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

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