Paper

  • Are Defenses for Graph Neural Networks Robust?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Defenses for Graph Neural Networks Robust?

    Felix Mujkanovic, Simon Geisler, Stephan GĂĽnnemann, Aleksandar Bojchevski p8954-8968 from Advances in Neural Information Processing Systems 35
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  • Are Diffusion Models Vision-And-Language Reasoners?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Diffusion Models Vision-And-Language Reasoners?

    Benno Krojer, Elinor Poole-Dayan, Vikram Voleti, Chris Pal, Siva Reddy p8385-8405 from Advances in Neural Information Processing Systems 36
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  • Are Emergent Abilities of Large Language Models a Mirage?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Emergent Abilities of Large Language Models a Mirage?

    Rylan Schaeffer, Brando Miranda, Sanmi Koyejo p55565-55581 from Advances in Neural Information Processing Systems 36
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  • Are GANs Overkill for NLP?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are GANs Overkill for NLP?

    David Alvarez-Melis, Vikas Garg, Adam Kalai p9072-9084 from Advances in Neural Information Processing Systems 35
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  • Are GATs Out of Balance?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are GATs Out of Balance?

    Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz p11430-11453 from Advances in Neural Information Processing Systems 36
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  • Are Graph Neural Networks Optimal Approximation Algorithms?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Are Graph Neural Networks Optimal Approximation Algorithms?

    Morris Yau, Nikolaos Karalias, Eric Lu, Jessica Xu, Stefanie Jegelka p73124-73181 from Advances in Neural Information Processing Systems 37
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  • 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, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang, Wenbing Huang 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?

    Mingtian Tan, Mike Merrill, Vinayak Gupta, Tim Althoff, Thomas Hartvigsen 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?

    Yizhang Zhu, Shiyin Du, Boyan Li, Yuyu Luo, Nan Tang 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?

    Lingao Xiao, Yang He 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

    Lingjiao Chen, Jared Davis, Boris Hanin, Peter Bailis, 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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