Oral Papers
1,594 papers found • Page 20 of 32
Conference
SAMPO: Scale-wise Autoregression with Motion Prompt for Generative World Models
Sen Wang, Jingyi Tian, Le Wang et al.
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella, Simon Bing, Jakob Runge
SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing
Mingfei Chen, Zijun Cui, Xiulong Liu et al.
Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
Baiting Luo, Ava Pettet, Aron Laszka et al.
Scalable inference of functional neural connectivity at submillisecond timescales
Arina Medvedeva, Edoardo Balzani, Alex Williams et al.
Scalable Mechanistic Neural Networks
Jiale Chen, Dingling Yao, Adeel Pervez et al.
Scaling and context steer LLMs along the same computational path as the human brain
Joséphine Raugel, Jérémy Rapin, Stéphane d'Ascoli et al.
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
Shikai Qiu, Lechao Xiao, Andrew Wilson et al.
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
Jie Cheng, Ruixi Qiao, ma yingwei et al.
Scaling up Masked Diffusion Models on Text
Shen Nie, Fengqi Zhu, Chao Du et al.
Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
CHUANQI CHENG, Jian Guan, Wei Wu et al.
ScatterAD: Temporal-Topological Scattering Mechanism for Time Series Anomaly Detection
Tao Yin, Shaochen Fu, Zhibin Zhang et al.
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
David K Park, Xihaier Luo, Guang Zhao et al.
Score-Based Diffusion Modeling for Nonparametric Empirical Bayes in Heteroscedastic Gaussian Mixtures
Gongyu Chen, Ying Cui
Score Matching with Missing Data
Josh Givens, Song Liu, Henry Reeve
SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space
Xupeng Zhu, Fan Wang, Robin Walters et al.
Seeing the Arrow of Time in Large Multimodal Models
Zihui (Sherry) Xue, Romy Luo, Kristen Grauman
See&Trek: Training-Free Spatial Prompting for Multimodal Large Language Model
Pengteng Li, Pinhao Song, Wuyang Li et al.
Selective Learning for Deep Time Series Forecasting
Yisong Fu, Zezhi Shao, Chengqing Yu et al.
Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization
Pritam Sarkar, Ali Etemad
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Qi Xu, Junyang Zhu, Dongdong Zhou et al.
Self-Improving Embodied Foundation Models
Seyed Kamyar Seyed Ghasemipour, Ayzaan Wahid, Jonathan Tompson et al.
Self-Perturbed Anomaly-Aware Graph Dynamics for Multivariate Time-Series Anomaly Detection
Jinyu Cai, Yuan Xie, Glynnis Lim et al.
Self-supervised contrastive learning performs non-linear system identification
Rodrigo Gonzalez Laiz, Tobias Schmidt, Steffen Schneider
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Chenxu Wu, Qingpeng Kong, Zihang Jiang et al.
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
Divyanshu Mishra, Mohammadreza Salehi, Pramit Saha et al.
Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
Tian-Shuo Liu, Xu-Hui Liu, Ruifeng Chen et al.
Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving
Xiang Li, Pengfei Li, Yupeng Zheng et al.
SEMPO: Lightweight Foundation Models for Time Series Forecasting
Hui He, Kun Yi, Yuanchi Ma et al.
SGN: Shifted Window-Based Hierarchical Variable Grouping for Multivariate Time Series Classification
Zenan Ying, Zhi Zheng, huijun hou et al.
S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models
Muzhi Dai, Chenxu Yang, Qingyi Si
Shallow Flow Matching for Coarse-to-Fine Text-to-Speech Synthesis
Dong Yang, YIYI CAI, Yuki Saito et al.
Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity
Daiyao Yi, Hao Dong, Michael Higley et al.
Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators
Srinath Dama, Kevin L Course, Prasanth B Nair
Show-o2: Improved Native Unified Multimodal Models
Jinheng Xie, Zhenheng Yang, Mike Zheng Shou
SIFusion: A Unified Fusion Framework for Multi-granularity Arctic Sea Ice Forecasting
Jingyi Xu, Shengnan Wang, Weidong Yang et al.
Simple and Efficient Heterogeneous Temporal Graph Neural Network
Yili Wang, Tairan Huang, Changlong He et al.
SimpleTM: A Simple Baseline for Multivariate Time Series Forecasting
Hui Chen, Viet Luong, Lopamudra Mukherjee et al.
Simplifying Deep Temporal Difference Learning
Matteo Gallici, Mattie Fellows, Benjamin Ellis et al.
Simulating Human-like Daily Activities with Desire-driven Autonomy
Yiding Wang, Yuxuan Chen, Fangwei Zhong et al.
Simulating Viva Voce Examinations to Evaluate Clinical Reasoning in Large Language Models
Christopher Chiu, Silviu Pitis, Mihaela van der Schaar
Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression
Yuning Shen, Lihao Wang, Huizhuo Yuan et al.
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar
SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs
Xin Su, Man Luo, Kris Pan et al.
Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling
Tianyu Liu, kai sun, Fuchun Sun et al.
SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
Wujiang Xu, Qitian Wu, Zujie Liang et al.
SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation
Yining Hong, Beide Liu, Maxine Wu et al.
SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction
Yang Zhou, Hao Shao, Letian Wang et al.
SMARTraj$^2$: A Stable Multi-City Adaptive Method for Multi-View Spatio-Temporal Trajectory Representation Learning
Tangwen Qian, Junhe Li, Yile Chen et al.