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  • LEACE: Perfect linear concept erasure in closed form

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LEACE: Perfect linear concept erasure in closed form

    Nora Belrose, Stella Biderman, Ryan Cotterell, Edward Raff, Shauli Ravfogel, David Schneider-Joseph p66044-66063 from Advances in Neural Information Processing Systems 36
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  • Lean Workbook: A large-scale Lean problem set formalized from natural language math problems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Lean Workbook: A large-scale Lean problem set formalized from natural language math problems

    Kai Chen, Yihan Geng, Dahua Lin, Jiayu Wang, Zijian Wu, Huaiyuan Ying p105848-105863 from Advances in Neural Information Processing Systems 37
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  • LeanDojo: Theorem Proving with Retrieval-Augmented Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LeanDojo: Theorem Proving with Retrieval-Augmented Language Models

    Animashree Anandkumar, Rahul Chalamala, Saad Godil, Alex Gu, Ryan J Prenger, Peiyang Song, Aidan Swope, Kaiyu Yang, Shixing Yu p21573-21612 from Advances in Neural Information Processing Systems 36
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  • Learn more, but bother less: parameter efficient continual learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn more, but bother less: parameter efficient continual learning

    Mehrdad Mahdavi, Fuli Qiao p97476-97498 from Advances in Neural Information Processing Systems 37
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  • Learn To be Efficient: Build Structured Sparsity in Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn To be Efficient: Build Structured Sparsity in Large Language Models

    Xiaoyan Bai, Beidi Chen, Fan Lai, Xueshen Liu, Z. Mao, Atul Prakash, Haizhong Zheng p101969-101991 from Advances in Neural Information Processing Systems 37
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  • Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery

    Hazel Doughty, Sarah Rastegar, Cees Snoek p72794-72818 from Advances in Neural Information Processing Systems 36
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  • Learn to Explain: Multimodal Reasoning Via Thought Chains for Science Question Answering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn to Explain: Multimodal Reasoning Via Thought Chains for Science Question Answering

    Kai-Wei Chang, Peter Clark, Ashwin Kalyan, Pan Lu, Swaroop Mishra, Liang Qiu, Oyvind Tafjord, Tanglin Xia, Song-Chun Zhu p2507-2521 from Advances in Neural Information Processing Systems 35
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  • Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets

    Michael Jordan, Yifei Min, Zhaoran Wang, Tianhao Wang, Ruitu Xu, Zhuoran Yang p19956-19970 from Advances in Neural Information Processing Systems 35
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  • Learn What Matters: Cross-Domain Imitation Learning with Task-Relevant Embeddings

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learn What Matters: Cross-Domain Imitation Learning with Task-Relevant Embeddings

    Tim Franzmeyer, João Henriques, Philip Torr p26283-26294 from Advances in Neural Information Processing Systems 35
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  • Learnability Matters: Active Learning for Video Captioning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learnability Matters: Active Learning for Video Captioning

    Jun Bao, Qiang Huang, Buyu Liu, Jun Yu, Min Zhang, Yiqian Zhang p37928-37954 from Advances in Neural Information Processing Systems 37
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  • Learnability of high-dimensional targets by two-parameter models and gradient flow

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learnability of high-dimensional targets by two-parameter models and gradient flow

    Dmitry Yarotsky p79144-79167 from Advances in Neural Information Processing Systems 37
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  • Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

    Minh Do, Teck-Yian Lim, Renan A. Rojas-Gomez, Alex Schwing, Raymond A. Yeh p35755-35768 from Advances in Neural Information Processing Systems 35
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