Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?

    Jiacheng Cen, Wenbing Huang, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang p26238-26266 from Advances in Neural Information Processing Systems 37
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  • Are Language Models Actually Useful for Time Series Forecasting?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Language Models Actually Useful for Time Series Forecasting?

    Tim Althoff, Vinayak Gupta, Thomas Hartvigsen, Mike Merrill, Mingtian Tan p60162-60191 from Advances in Neural Information Processing Systems 37
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  • Are Large Language Models Good Statisticians?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Large Language Models Good Statisticians?

    Shiyin Du, Boyan Li, Yuyu Luo, Nan Tang, Yizhang Zhu p62697-62731 from Advances in Neural Information Processing Systems 37
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  • Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?

    Yang He, Lingao Xiao p16406-16437 from Advances in Neural Information Processing Systems 37
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  • Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems

    Peter Bailis, Lingjiao Chen, Jared Davis, Boris Hanin, Ion Stoica, Matei Zaharia, James Zou p45767-45790 from Advances in Neural Information Processing Systems 37
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  • Are Multiple Instance Learning Algorithms Learnable for Instances?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Multiple Instance Learning Algorithms Learnable for Instances?

    Jaeseok Jang, Hyuk-Yoon Kwon p10575-10612 from Advances in Neural Information Processing Systems 37
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  • Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology

    Alexander Binder, Andreas Kleppe, Dhananjay Tomar p43499-43532 from Advances in Neural Information Processing Systems 37
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  • Are Self-Attentions Effective for Time Series Forecasting?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Self-Attentions Effective for Time Series Forecasting?

    Dongbin Kim, Hoki Kim, Jaewook Lee, Jinseong Park p114180-114209 from Advances in Neural Information Processing Systems 37
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  • Are These the Same Apple? Comparing Images Based on Object Intrinsics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are These the Same Apple? Comparing Images Based on Object Intrinsics

    Klemen Kotar, Stephen Tian, Jiajun Wu, Dan Yamins, Hong-Xing Yu p40853-40871 from Advances in Neural Information Processing Systems 36
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  • Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks

    Krishnaram Kenthapadi, Matthäus Kleindessner, Francesco Locatello, Michael Lohaus, Chris Russell p16548-16562 from Advances in Neural Information Processing Systems 35
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  • Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?

    Yuheng Bu, Subhro Das, Soumya Ghosh, J. Ryu, Prasanna Sattigeri, Maohao Shen, Gregory Wornell p107830-107864 from Advances in Neural Information Processing Systems 37
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  • Are Vision Transformers More Data Hungry Than Newborn Visual Systems?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Vision Transformers More Data Hungry Than Newborn Visual Systems?

    Lalit Pandey, Justin Wood, Samantha Wood p73104-73121 from Advances in Neural Information Processing Systems 36
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  • Are We on the Right Way for Evaluating Large Vision-Language Models?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are We on the Right Way for Evaluating Large Vision-Language Models?

    Lin Chen, Zehui Chen, Xiaoyi Dong, Haodong Duan, Jinsong Li, Dahua Lin, Yu Qiao, Jiaqi Wang, Yuhang Zang, Pan Zhang, Feng Zhao p27056-27087 from Advances in Neural Information Processing Systems 37
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  • Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks

    Jiyang Guan, Ran He, Jian Liang p36571-36584 from Advances in Neural Information Processing Systems 35
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  • Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections

    Nuo Chen, Hong Huang, Hai Jin, Zihan Luo, Jiping Zhang, Yongkang Zhou p71568-71595 from Advances in Neural Information Processing Systems 37
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  • ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction

    Beiquan Cao, Renze Chen, Meng Li, Xiuhong Li, Yun Liang, Zhuofeng Wang, Xuechao Wei, Tong Wu, Shengen Yan, Size Zheng p113134-113155 from Advances in Neural Information Processing Systems 37
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  • AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields

    Patrick Gallinari, Etienne Le Naour, Louis Serrano, Jean-Noël Vittaut, Thomas X Wang p13489-13521 from Advances in Neural Information Processing Systems 37
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  • ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

    Kangjie Chen, Guanlin Li, Jie Zhang, Shudong Zhang, Tianwei Zhang p91184-91219 from Advances in Neural Information Processing Systems 37
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  • Artemis: Towards Referential Understanding in Complex Videos

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Artemis: Towards Referential Understanding in Complex Videos

    David Doermann, Tianren Ma, Jihao Qiu, Xi Tang, Yunjie Tian, Lingxi Xie, Pengyu Yan, Qixiang Ye, Yuan Zhang p114321-114347 from Advances in Neural Information Processing Systems 37
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  • ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections

    Wei-Chih Hung, Varun Jampani, Yuanzhen Li, Amit Raj, Michael Rubinstein, Ming-Hsuan Yang, Chun-Han Yao p48173-48184 from Advances in Neural Information Processing Systems 36
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  • Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis

    Hakan Bilen, Jianning Deng, Kartic Subr p119717-119741 from Advances in Neural Information Processing Systems 37
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  • Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

    Jonathan Cook, Jakob Foerster, Edward Hughes, Joel Leibo, Chris Lu p59689-59715 from Advances in Neural Information Processing Systems 37
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  • ARTree: A Deep Autoregressive Model for Phylogenetic Inference

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ARTree: A Deep Autoregressive Model for Phylogenetic Inference

    Tianyu Xie, Cheng Zhang p14427-14444 from Advances in Neural Information Processing Systems 36
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  • AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation

    Junli Cao, Jierun Chen, Huseyin Coskun, Anil Kag, Willi Menapace, Jian Ren, Aliaksandr Siarohin, Sergey Tulyakov p65119-65153 from Advances in Neural Information Processing Systems 37
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