Papers

Deep, long-form breakdowns of recent research in AI, machine learning, security & programming languages.

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ai Oct 02 The Missing Primitive: Diagnosing and Repairing Mathematical Reasoning in Large Language Models by Shuo Xing, Zilin Dai, Chengyuan Qian, Fangzhou Lin, Wenjing Chen, Ping He, Pan Lu, Alvaro Velasquez, Mohit Bansal, Zhengzhong Tu machine learning Oct 02 Trust the Direction, Search the Step: Zero-and-First-Order Methods for LLM Fine-Tuning by Cristian McGee, El Houcine Bergou, Aritra Dutta machine learning Oct 02 Generative modeling of intrinsically disordered protein regions by reinforcing sparse autoencoder features by Jason X. Liu, Sebastian Ibarraran, Frank Hu, Soojung Yang, Xinyu A. Feng, Abigail Park, Anagha Aneesh, Lacramioara Bintu, Alexander R. Dunn, Grant M. Rotskoff ai Oct 02 Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry by Yiming Huang, Yujie Zeng, Vijay Prakash Dwivedi, Simone Foti, Jianmin Wang, Jure Leskovec, Tolga Birdal machine learning Oct 02 Decoding Looped Transformers Better for (Almost) Free by Weihao Liu, Huangjie Zheng, Tianrong Chen, Rohit Dilip, Richard He Bai, Yizhu Jiao, Yuyang Wang, Ruixiang Zhang machine learning Oct 02 SoftServe: A Scalable Quasi-Newton Method for Deep Learning by Joohwan Ko, Tetiana Parshakova, Diana Cai, Robert M. Gower machine learning Oct 02 From Gradients to Capabilities: Understanding Multi-Teacher On-Policy Distillation by Siqi Zhu, Suozhi Huang, Kaixuan Zhang, Yuheng Yang, Zhanyang Jin, Yihang Sun, Jiaxuan You machine learning Oct 02 Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes by Jianru Shen machine learning Oct 02 Every Ablation Is a Dose: Counterweights and the Semblance of Self-Repair by Areeb Ahmad, Pratinav Seth, Vinay Kumar Sankarapu machine learning Oct 02 When Do Intrinsic Rewards Lead to Exploration? by Scott W. Viteri (Stanford University), Laura Gomezjurado Gonzalez (Stanford University), Clark Barrett (Stanford University)