Papers
16,137 papers found
Annealed Relaxation of Speculative Decoding for Faster Autoregressive Image Generation
Xingyao Li, Fengzhuo Zhang, Cunxiao Du et al.
DeepBooTS: Dual-Stream Residual Boosting for Drift-Resilient Time-Series Forecasting
Daojun Liang, Jing Chen, Xiao Wang et al.
Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
Jinhao Liang, Sven Koenig, Ferdinando Fioretto
Views Attention Fusion of Granular-ball Fuzzy Representations Split for Improved Multi-view Clustering
Shuaiyu Liu, Song Wu, Jie Xu et al.
Sparse-Scale Transformer with Bidirectional Awareness for Time Series Forecasting
Ying Liu, Bo Liu, Sheng Huang et al.
Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs
Yuxuan Liu, Wenchao Xu, Haozhao Wang et al.
Scaling Law for Large Wireless Models
Ziheng Liu, Jiayi Zhang, Haoyu Wang et al.
Spiking-Aided Neural Architecture for Efficient and Robust WiFi Sensing
Yisha Lu, Liwen Jing, Jiangmao Zheng et al.
Attention Retention for Continual Learning with Vision Transformers
Yue Lu, Xiangyu Zhou, Shizhou Zhang et al.
Quantum Algorithms for Spectral Sums
Alessandro Luongo, Changpeng Shao
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
Sisuo Lyu, Siru Zhong, Weilin Ruan et al.
Semantic-Aware Feature Enhancement for Partial Label Learning
Haowei Mei, Chao Zhang, Wentao Fan et al.
RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences
Abinay Reddy Naini, Fernando Diaz, Carlos Busso
Robust Semi-paired Multimodal Learning for Cross-modal Retrieval
Yang Qin, Yuan Sun, Xi Peng et al.
Catastrophic Forgetting in Kolmogorov-Arnold Networks
Mohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou et al.
TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting
Chuanru Ren, Yao Lu, Tianjin Huang et al.
HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems
Ricardo G. Sanfelice
HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting
Andrey Savchenko, Oleg Kachan
Graph-Conditional Flow Matching for Relational Data Generation
Davide Scassola, Sebastiano Saccani, Luca Bortolussi
Sonnet: Spectral Operator Neural Network for Multivariable Time Series Forecasting
Yuxuan Shu, Vasileios Lampos
MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
Dimitrios Sinodinos, Jack Yi Wei, Narges Armanfard
Synthetic Forgetting Without Access: A Few-Shot Zero-Glance Framework for Machine Unlearning
Qipeng Song, Nan Yang, Ziqi Xu et al.
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
Hong Ye Tan, Subhadip Mukherjee, Junqi Tang et al.
Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
Dahao Tang, Nan Yang, Yanli Li et al.
Learning Conjugate Direction Fields for Planar Quadrilateral Mesh Generation
Jiong Tao, Yong-Liang Yang, Bailin Deng