Paper

  • Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models

    Jiangang Lu, Xuehao Wang, Ying Wei, Yu Zhang, Yulong Zhang, Zhan Zhuang p73920-73951 from Advances in Neural Information Processing Systems 37
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  • Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

    Marc Brockschmidt, Tor Fjelde, Andrew Foong, Leon Klein, Bruno Mlodozeniec, Frank Noe, Sebastian Nowozin, Ryota Tomioka p52863-52883 from Advances in Neural Information Processing Systems 36
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  • TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

    Jiaxiang Dong, Yong Liu, Mingsheng Long, Guo Qin, Yunzhong Qiu, Jianmin Wang, Yuxuan Wang, Haixu Wu, Haoran Zhang p469-498 from Advances in Neural Information Processing Systems 37
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  • Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

    Pankaj Dayama, Vijay Ekambaram, Wesley Gifford, Arindam Jati, Jayant Kalagnanam, Sumanta Mukherjee, Nam Nguyen, Chandra Reddy p74147-74181 from Advances in Neural Information Processing Systems 37
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  • TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge

    Lin Gu, Juntao Guan, Rui Lai, Huanan Li, Sijun Ma, Zhangming Zhu p85340-85359 from Advances in Neural Information Processing Systems 37
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  • TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices

    Ting Dang, Hong Jia, Young Kwon, Cecilia Mascolo, Alessio Orsino, Domenico Talia p43274-43299 from Advances in Neural Information Processing Systems 37
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  • TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

    Xi Chen, Lu Qi, Yu Qiao, Kun Wang, Yi Wang, Hengshuang Zhao, Rongkun Zheng p38844-38862 from Advances in Neural Information Processing Systems 36
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  • To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty

    András György, Ilja Kuzborskij, Csaba Szepesvári, Yasin Yadkori p58077-58117 from Advances in Neural Information Processing Systems 37
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  • To Err Like Human: Affective Bias-Inspired Measures for Visual Emotion Recognition Evaluation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    To Err Like Human: Affective Bias-Inspired Measures for Visual Emotion Recognition Evaluation

    Liqiang Nie, Jinglei Shi, Jufeng Yang, Chenxi Zhao p134747-134769 from Advances in Neural Information Processing Systems 37
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  • To Learn or Not to Learn, That is the Question — A Feature-Task Dual Learning Model of Perceptual Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    To Learn or Not to Learn, That is the Question — A Feature-Task Dual Learning Model of Perceptual Learning

    Xiao Liu, Muyang Lyu, Si Wu, Cong Yu p37736-37764 from Advances in Neural Information Processing Systems 37
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  • To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis

    Yao Fu, Fuzhao Xue, Yang You, Zangwei Zheng, Wangchunshu Zhou p59304-59322 from Advances in Neural Information Processing Systems 36
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  • To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning

    Ekaterina Lobacheva, Dmitrii Pozdeev, Ildus Sadrtdinov, Dmitry Vetrov p15936-15964 from Advances in Neural Information Processing Systems 36
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