Papers
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation
Jeffrey Willette, Seanie Lee, Bruno Andreis et al.
Scaling Laws for Generative Mixed-Modal Language Models
Armen Aghajanyan, Lili Yu, Alexis Conneau et al.
Scaling Laws for Multilingual Neural Machine Translation
Patrick Fernandes, Behrooz Ghorbani, Xavier Garcia et al.
Scaling Laws for Reward Model Overoptimization
Leo Gao, John Schulman, Jacob Hilton
Scaling of Class-wise Training Losses for Post-hoc Calibration
Seungjin Jung, Seungmo Seo, Yonghyun Jeong et al.
Scaling Spherical CNNs
Carlos Esteves, Jean-Jacques Slotine, Ameesh Makadia
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory
Justin Cui, Ruochen Wang, Si Si et al.
Scaling Vision Transformers to 22 Billion Parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa et al.
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
Minshuo Chen, Kaixuan Huang, Tuo Zhao et al.
SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation
Shikun Sun, Longhui Wei, Junliang Xing et al.
SE(3) diffusion model with application to protein backbone generation
Jason Yim, Brian L. Trippe, Valentin De Bortoli et al.
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
Taoan Huang, Aaron M Ferber, Yuandong Tian et al.
Second-Order Optimization with Lazy Hessians
Nikita Doikov, El Mahdi Chayti, Martin Jaggi
Second-order regression models exhibit progressive sharpening to the edge of stability
Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington
Secure Federated Correlation Test and Entropy Estimation
Qi Pang, Lun Wang, Shuai Wang et al.
SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching
Liren Yu, Jiaming Xu, Xiaojun Lin
SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning
Junran Wu, Xueyuan Chen, Bowen Shi et al.
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation
Huaishao Luo, Junwei Bao, Youzheng Wu et al.
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction
Khai Nguyen, Dang Nguyen, Nhat Ho
Self-Interpretable Time Series Prediction with Counterfactual Explanations
Jingquan Yan, Hao Wang
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
Vishwaraj Doshi, Jie Hu, Do Young Eun
Self-supervised learning of Split Invariant Equivariant representations
Quentin Garrido, Laurent Najman, Yann Lecun
Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations
Weiwei Lin, Chenhang He, Man-Wai Mak et al.
SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models
Shenghua Wan, Yucen Wang, Minghao Shao et al.
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows
Phillip Si, Zeyi Chen, Subham Sekhar Sahoo et al.