Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Frieren: Efficient Video-to-Audio Generation Network with Rectified Flow Matching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Frieren: Efficient Video-to-Audio Generation Network with Rectified Flow Matching

    Yongqi Wang, Wenxiang Guo, Rongjie Huang, Jiawei Huang, Zehan Wang, Fuming You, Ruiqi Li, Zhou Zhao p128118-128138 from Advances in Neural Information Processing Systems 37
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  • From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos

    Matthew Wallingford, Anand Bhattad, Aditya Kusupati, Vivek Ramanujan, Matt Deitke, Sham Kakade, Aniruddha Kembhavi, Roozbeh Mottaghi, Wei-Chiu Ma, Ali Farhadi p17743-17760 from Advances in Neural Information Processing Systems 37
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  • From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach

    Timothée Devergne, Vladimir Kostic, Michele Parrinello, Massimiliano Pontil p75495-75521 from Advances in Neural Information Processing Systems 37
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  • From Causal to Concept-Based Representation Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Causal to Concept-Based Representation Learning

    Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar p101250-101296 from Advances in Neural Information Processing Systems 37
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  • From Chaos to Clarity: 3DGS in the Dark

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Chaos to Clarity: 3DGS in the Dark

    Zhihao Li, Yufei Wang, Alex Kot, Bihan Wen p94971-94992 from Advances in Neural Information Processing Systems 37
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  • From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Models to Pre-trained Machine Reader

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Models to Pre-trained Machine Reader

    Weiwen Xu, Xin Li, Wenxuan Zhang, Meng Zhou, Wai Lam, Luo Si, Lidong Bing p67309-67328 from Advances in Neural Information Processing Systems 36
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  • From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement

    Zhibin Gu, Songhe Feng p103545-103573 from Advances in Neural Information Processing Systems 37
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  • From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion

    Robin San Roman, Yossi Adi, Antoine Deleforge, Romain Serizel, Gabriel Synnaeve, Alexandre Defossez p1526-1538 from Advances in Neural Information Processing Systems 36
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  • From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent

    Christopher De Sa, Satyen Kale, Jason Lee, Ayush Sekhari, Karthik Sridharan p30963-30976 from Advances in Neural Information Processing Systems 35
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  • From Instance Training to Instruction Learning: Task Adapters Generation from Instructions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Instance Training to Instruction Learning: Task Adapters Generation from Instructions

    Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Yanchao Hao, Shengping Liu, Kang Liu, Jun Zhao p45552-45577 from Advances in Neural Information Processing Systems 37
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  • From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

    Mohammad Pedramfar, Vaneet Aggarwal p37626-37664 from Advances in Neural Information Processing Systems 37
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  • From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection

    Xinlei Wang, Maike Feng, Jing Qiu, Jinjin Gu, Junhua Zhao p58118-58153 from Advances in Neural Information Processing Systems 37
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  • From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces

    Peter Shaw, Mandar Joshi, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, Kristina N Toutanova p34354-34370 from Advances in Neural Information Processing Systems 36
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  • From Similarity to Superiority: Channel Clustering for Time Series Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Similarity to Superiority: Channel Clustering for Time Series Forecasting

    Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying p130635-130663 from Advances in Neural Information Processing Systems 37
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  • From Tempered to Benign Overfitting in ReLU Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Tempered to Benign Overfitting in ReLU Neural Networks

    Guy Kornowski, Gilad Yehudai, Ohad Shamir p58011-58046 from Advances in Neural Information Processing Systems 36
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  • From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning

    Pusen Dong, Tianchen Zhu, Yue Qiu, Haoyi Zhou, Jianxin Li p125635-125662 from Advances in Neural Information Processing Systems 37
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  • From Trainable Negative Depth to Edge Heterophily in Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Trainable Negative Depth to Edge Heterophily in Graphs

    Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong p70162-70178 from Advances in Neural Information Processing Systems 36
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  • From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $\alpha$-NeuS

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $\alpha$-NeuS

    Haoran Zhang, Junkai Deng, Xuhui Chen, Fei Hou, Wencheng Wang, Hong Qin, Chen Qian, Ying He p28078-28102 from Advances in Neural Information Processing Systems 37
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  • From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models

    Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Zhao, Ramana Kompella, Sijia Liu p82265-82295 from Advances in Neural Information Processing Systems 37
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  • From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When

    Kevin Christian Wibisono, Yixin Wang p16369-16405 from Advances in Neural Information Processing Systems 37
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  • From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models

    Roy Uziel, Or Dinari, Oren Freifeld p10995-11007 from Advances in Neural Information Processing Systems 36
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  • Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

    Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu p43800-43825 from Advances in Neural Information Processing Systems 36
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  • Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models

    Shenghao Fu, Junkai Yan, Qize Yang, Xihan Wei, Xiaohua Xie, Wei-Shi Zheng p105949-105971 from Advances in Neural Information Processing Systems 37
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  • Frustratingly Easy Test-Time Adaptation of Vision-Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Frustratingly Easy Test-Time Adaptation of Vision-Language Models

    Matteo Farina, Gianni Franchi, Giovanni Iacca, Massimiliano Mancini, Elisa Ricci p129062-129093 from Advances in Neural Information Processing Systems 37
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