3 papers
math.OC2025
Clapping: Removing Per-sample Storage for Pipeline Parallel Distributed Optimization with Communication Compression
Boao Kong, Xu Huang, Yuqi Xu +3
Pipeline-parallel distributed optimization is essential for large-scale machine learning but is challenged by significant communication overhead from transmitting high-dimensional…
cs.LG2025
An Efficient Subspace Algorithm for Federated Learning on Heterogeneous Data
Jiaojiao Zhang, Yuqi Xu, Kun Yuan
This work addresses the key challenges of applying federated learning to large-scale deep neural networks, particularly the issue of client drift due to data heterogeneity across c…
cs.CV2025
VISTAR:A User-Centric and Role-Driven Benchmark for Text-to-Image Evaluation
Kaiyuan Jiang, Ruoxi Sun, Ying Cao +4
We present VISTAR, a user-centric, multi-dimensional benchmark for text-to-image (T2I) evaluation that addresses the limitations of existing metrics. VISTAR introduces a two-tier h…