Papers
Scalable First-order Method for Certifying Optimal k-Sparse GLMs
Jiachang Liu, Soroosh Shafiee, Andrea Lodi
Scalable Gaussian Processes with Latent Kronecker Structure
Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat et al.
Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
Tinglin Huang, Tianyu Liu, Mehrtash Babadi et al.
Scalable Meta-Learning via Mixed-Mode Differentiation
Iurii Kemaev, Dan A. Calian, Luisa M Zintgraf et al.
Scalable Model Merging with Progressive Layer-wise Distillation
Jing Xu, Jiazheng Li, Jingzhao Zhang
Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment
Yuhui Ding, Thomas Hofmann
Scalable Private Partition Selection via Adaptive Weighting
Justin Y. Chen, Vincent Cohen-Addad, Alessandro Epasto et al.
Scalable Sobolev IPM for Probability Measures on a Graph
Tam Le, Truyen Nguyen, Hideitsu Hino et al.
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
Shikai Qiu, Lechao Xiao, Andrew Gordon Wilson et al.
Scaling Inference-Efficient Language Models
Song Bian, Minghao Yan, Shivaram Venkataraman
Scaling Large Motion Models with Million-Level Human Motions
Ye Wang, Sipeng Zheng, Bin Cao et al.
Scaling Laws for Differentially Private Language Models
Ryan Mckenna, Yangsibo Huang, Amer Sinha et al.
Scaling Laws for Floating–Point Quantization Training
Xingwu Sun, Shuaipeng Li, Ruobing Xie et al.
Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge et al.
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell et al.
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
Scaling Laws for Upcycling Mixture-of-Experts Language Models
Seng Pei Liew, Takuya Kato, Sho Takase
Scaling Laws in Patchification: An Image Is Worth 50,176 Tokens And More
Feng Wang, Yaodong Yu, Wei Shao et al.
Scaling Probabilistic Circuits via Monarch Matrices
Honghua Zhang, Meihua Dang, Benjie Wang et al.
Scaling Sparse Feature Circuits For Studying In-Context Learning
Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.
Scaling Test-Time Compute Without Verification or RL is Suboptimal
Amrith Setlur, Nived Rajaraman, Sergey Levine et al.
Scaling Trends in Language Model Robustness
Nikolaus H. R. Howe, Ian R. Mckenzie, Oskar John Hollinsworth et al.
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
Yuhui Wang, Qingyuan Wu, Dylan R. Ashley et al.
Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
Chuanqi Cheng, Jian Guan, Wei Wu et al.
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
Nikolaos Chaidos, Angeliki Dimitriou, Maria Lymperaiou et al.