Paper

  • RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

    Pengfei Cao, Yubo Chen, Zhitao He, Zhuoran jin, Jiachun Li, Kang Liu, Chenhao Wang, Hongbang Yuan, Jun Zhao p98213-98263 from Advances in Neural Information Processing Systems 37
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  • S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity

    Beidi Chen, Geyang Guo, Jixuan Leng, Ryumei Nakada, Xinyu Yang, Huaxiu Yao, Linjun Zhang, Jiawei Zhao p59912-59947 from Advances in Neural Information Processing Systems 37
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  • S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

    Minkyu Kim, Kyungmin Lee, Sangwoo Mo, Jinwoo Shin p61187-61212 from Advances in Neural Information Processing Systems 36
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  • S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search

    Zhifeng Gao, Guolin Ke, Zhen Wang, Zhewei Wei, Feng Yu, Gengmo Zhou p74715-74737 from Advances in Neural Information Processing Systems 37
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  • S-PIFu: Integrating Parametric Human Models with PIFu for Single-View Clothed Human Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-PIFu: Integrating Parametric Human Models with PIFu for Single-View Clothed Human Reconstruction

    Kennard Chan, Guosheng Lin, Weisi Lin, Haiyu Zhao p17373-17385 from Advances in Neural Information Processing Systems 35
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  • S-Prompts Learning with Pre-Trained Transformers: An Occam’s Razor for Domain Incremental Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-Prompts Learning with Pre-Trained Transformers: An Occam’s Razor for Domain Incremental Learning

    Xiaopeng Hong, Zhiwu Huang, Yabin Wang p5682-5695 from Advances in Neural Information Processing Systems 35
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  • S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization

    Yuehaw Khoo, Mathias Oster, Richard Zhu p61621-61657 from Advances in Neural Information Processing Systems 37
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  • S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training

    Jianfei Chen, Yuezhou Hu, Jun Zhu p33756-33778 from Advances in Neural Information Processing Systems 37
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  • S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning

    Tao Chen, Weihao Lin, Shengji Tang, Peng Ye, Chong Yu p116547-116574 from Advances in Neural Information Processing Systems 37
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  • S2P: State-Conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S2P: State-Conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning

    Daesol Cho, H. Jin Kim, Dongseok Shim p11534-11546 from Advances in Neural Information Processing Systems 35
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  • S3GC: Scalable Self-Supervised Graph Clustering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S3GC: Scalable Self-Supervised Graph Clustering

    Fnu Devvrit, Inderjit Dhillon, Prateek Jain, Aditya Sinha p3248-3261 from Advances in Neural Information Processing Systems 35
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  • S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces

    Stephen Baccus, Tri Dao, Gordon Downs, Karan Goel, Albert Gu, Eric Nguyen, Christopher Ré, Preey Shah p2846-2861 from Advances in Neural Information Processing Systems 35
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