All Papers
34,598 papers found • Page 640 of 692
Conference
Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers
Ruiyuan Zhang, Jiaxiang Liu, Zexi Li et al.
Scalable Group Choreography via Variational Phase Manifold Learning
Nhat Le, Khoa Do, Xuan Bui et al.
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Katherine Crowson, Stefan Baumann, Alex Birch et al.
Scalable Language Model with Generalized Continual Learning
Bohao PENG, Zhuotao Tian, Shu Liu et al.
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing
Minyang Hu, Hong Chang, Bingpeng Ma et al.
Scalable Monotonic Neural Networks
Hyunho Kim, Jong-Seok Lee
Scalable Motion Style Transfer with Constrained Diffusion Generation
Wenjie Yin, Yi Yu, Hang Yin et al.
Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
Weixuan Liang, En Zhu, Shengju Yu et al.
Scalable Neural Network Kernels
Arijit Sehanobish, Krzysztof Choromanski, YUNFAN ZHAO et al.
Scalable Online Exploration via Coverability
Philip Amortila, Dylan Foster, Akshay Krishnamurthy
Scalable Pre-training of Large Autoregressive Image Models
Alaaeldin Ali, Michal Klein, Shuangfei Zhai et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard Sutton et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard Sutton et al.
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs
Federico Bianchi, Edoardo Zorzi, Alberto Castellini et al.
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Scalar Function Topology Divergence: Comparing Topology of 3D Objects
Ilya Trofimov, Daria Voronkova, Eduard Tulchinskii et al.
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Jijin Hu, Ke Li, Yonggang Qi et al.
ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models
Yingqing He, Shaoshu Yang, Haoxin Chen et al.
Scaled Decoupled Distillation
Shicai Wei, Chunbo Luo, Yang Luo
ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation
Zhiyuan MA, Yuxiang WEI, Yabin Zhang et al.
Scale-Free Image Keypoints Using Differentiable Persistent Homology
Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno et al.
Scale Optimization Using Evolutionary Reinforcement Learning for Object Detection on Drone Imagery
Jialu Zhang, Xiaoying Yang, Wentao He et al.
Scaling and Masking: A New Paradigm of Data Sampling for Image and Video Quality Assessment
Yongxu Liu, Yinghui Quan, Guoyao Xiao et al.
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
Xin Li, Jing Yu Koh, Alexander Ku et al.
Scaling Backwards: Minimal Synthetic Pre-training?
Ryo Nakamura, Ryu Tadokoro, Ryosuke Yamada et al.
Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
Yechan Kim, Hwijoon Lim, Dongsu Han
Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.
Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
Lucas Nunes, Rodrigo Marcuzzi, Benedikt Mersch et al.
Scaling Down Deep Learning with MNIST-1D
Sam Greydanus, Dmitry Kobak
Scaling Exponents Across Parameterizations and Optimizers
Katie Everett, Lechao Xiao, Mitchell Wortsman et al.
Scaling Few-Shot Learning for the Open World
Zhipeng Lin, Wenjing Yang, Haotian Wang et al.
Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
Kai Xu, Rongyu Chen, Gianni Franchi et al.
Scaling Laws for Associative Memories
Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
Scaling Laws for Data Filtering— Data Curation cannot be Compute Agnostic
Sachin Goyal, Pratyush Maini, Zachary Lipton et al.
Scaling Laws for Fine-Grained Mixture of Experts
Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.
Scaling Laws for Sparsely-Connected Foundation Models
Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby et al.
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert, Wenlong Ji, Tatsunori Hashimoto et al.
Scaling Laws of RoPE-based Extrapolation
Xiaoran Liu, Hang Yan, Chenxin An et al.
Scaling Laws of Synthetic Images for Model Training ... for Now
Lijie Fan, Kaifeng Chen, Dilip Krishnan et al.
Scaling physics-informed hard constraints with mixture-of-experts
Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann et al.
Scaling Speech Technology to 1,000+ Languages
Vineel Pratap Konduru, Andros Tjandra, Bowen Shi et al.
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma, Jibin Wu, Chenyang Si et al.
Scaling Tractable Probabilistic Circuits: A Systems Perspective
Anji Liu, Kareem Ahmed, Guy Van den Broeck
Scaling Up Dynamic Human-Scene Interaction Modeling
Nan Jiang, Zhiyuan Zhang, Hongjie Li et al.
Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization
Jooyeol Yun, Choo Jaegul
Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
Shuvendu Roy, Ali Etemad
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Fanghua Yu, Jinjin Gu, Zheyuan Li et al.
Scaling Up Video Summarization Pretraining with Large Language Models
Dawit Argaw Argaw, Seunghyun Yoon, Fabian Caba Heilbron et al.
ScanERU: Interactive 3D Visual Grounding Based on Embodied Reference Understanding
Ziyang Lu, Yunqiang Pei, Guoqing Wang et al.