Paper

  • 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 WOOD BUILDINGS MORE CIRCULAR? A COMPARATIVE STUDY ON BUILDING CIRCULARITY BETWEEN REINFORCED CONCRETE AND TIMBER STRUCTURES

    World Conference on Timber Engineering 2025

    ARE WOOD BUILDINGS MORE CIRCULAR? A COMPARATIVE STUDY ON BUILDING CIRCULARITY BETWEEN REINFORCED CONCRETE AND TIMBER STRUCTURES

    Harrison Huang, Lu Li, Yan Gu p3009-3016 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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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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  • Area of Coverage and Sizing Definitions of Personal Armour for UK Armed Forces Personnel

    Royal Military Academy (Belgium)

    Area of Coverage and Sizing Definitions of Personal Armour for UK Armed Forces Personnel

    R. Fryer, J. Breeze, E. Lewis p401-410 from Personal Armour Systems Symposium. 2020. (PDF)
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  • ARENA BLAST TESTING OF REINFORCED CROSS-LAMINATED TIMBER

    World Conference on Timber Engineering 2025

    ARENA BLAST TESTING OF REINFORCED CROSS-LAMINATED TIMBER

    Eric Kjolsing, Mark Weaver, Jalen Johnson, Marco Lo Ricco p491-500 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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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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