large-scale training

A Large-scale Training Paradigm for Graph Generative Models ICLR 2025 Scale Efficient Training for Large Datasets CVPR 2025 SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs ICML 2025 InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks CVPR 2024 No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance NeurIPS 2024 Revisiting Adversarial Training at Scale CVPR 2024 DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training CVPR 2023 Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation ICCV 2023 Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale NeurIPS 2023 A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking NeurIPS 2022 An Efficient Training Approach for Very Large Scale Face Recognition CVPR 2022 GraphFM: Improving Large-Scale GNN Training via Feature Momentum ICML 2022 Swin Transformer V2: Scaling Up Capacity and Resolution CVPR 2022 TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training NeurIPS 2022 SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement NeurIPS 2021 Structure-Aware Face Clustering on a Large-Scale Graph With 107 Nodes CVPR 2021 Virtual Fully-Connected Layer: Training a Large-Scale Face Recognition Dataset With Limited Computational Resources CVPR 2021 Exploring Transformers for Large-Scale Speech Recognition Interspeech 2020 BLAS-on-flash: An Efficient Alternative for Large Scale ML Training and Inference? NSDI 2019 GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism NeurIPS 2019 Hard Mixtures of Experts for Large Scale Weakly Supervised Vision CVPR 2017 Tree Decomposition for Large-Scale SVM Problems JMLR 2010 Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" JMLR 2007