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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, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman 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

    Huaiyuan Ying, Zijian Wu, Yihan Geng, Jiayu Wang, Dahua Lin, Kai Chen 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

    Kaiyu Yang, Aidan Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan J Prenger, Animashree Anandkumar 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

    Fuli Qiao, Mehrdad Mahdavi 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

    Haizhong Zheng, Xiaoyan Bai, Xueshen Liu, Z. Mao, Beidi Chen, Fan Lai, Atul Prakash 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

    Sarah Rastegar, Hazel Doughty, 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

    Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, Ashwin Kalyan 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

    Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael Jordan, 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, Philip Torr, João Henriques 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

    Yiqian Zhang, Buyu Liu, Jun Bao, Qiang Huang, Min Zhang, Jun Yu 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

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