NeurIPS

Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection

Chengcan Wu, Zeming Wei, Huanran Chen, Yinpeng Dong, Meng Sun

机构 * Peking University（北京大学） ； Tsinghua University（清华大学） 纠错

Comments 10 pages, 9 figures, Under review as a full paper at AAAI 2026. A preliminary version is under review at the NeurIPS 2025 Workshop on Reliable ML from Unreliable Data

Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work

Aviv Ovadya, Kyle Redman, Luke Thorburn, Quan Ze Chen, Oliver Smith, Flynn Devine, Andrew Konya, Smitha Milli, Manon Revel, K. J. Kevin Feng, Amy X. Zhang, Bilva Chandra, Michiel A. Bakker, Atoosa Kasirzadeh

Comments 31 pages. Accepted to the position paper track at ICML 2025. A previous version was presented at the Pluralistic Alignment Workshop at NeurIPS 2024. For ongoing work, see: https://democracylevels.org

Geometry-aware training of factorized layers in tensor Tucker format

Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco

机构 * School of Mathematics, Gran Sasso Science Institute（格兰萨索科学研究所数学系） ； Computer Science and Mathematics Division, Oak Ridge National Laboratory（橡树岭国家实验室计算机科学与数学部） ； Department of Mathematics, University of Innsbruck（因斯布鲁克大学数学系） ； Department of Data Science, Norwegian University of Life Sciences（挪威生命科学大学数据科学系） ； School of Mathematics and Maxwell Institute, University of Edinburgh（爱丁堡大学数学系和麦克斯韦研究所） 纠错

Journal ref Proceedings NeurIPS 2024