3 papers
cs.CV2026
RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers
Mengyuan Fan, Bokai Huang, JiaMing Pan +4
Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections and attention computations…
cs.DC2026
HAPMoE: Heterogeneity-Aware Automatic Parallelism Planning for Mixture-of-Experts Models Training
Mengyuan Fan, Peizhuang Cong, Zixiao Huang +7
As model sizes continue to scale, distributed training has become inevitable. Automatic parallelization techniques can derive efficient training parallelism strategies at low cost…
cs.SE2026
ForgeTrain: Forging Production-Grade Training Frameworks via Harness-Driven AI Development
Qingfeng He, Zhui Zhu, Shangzhan Li +15
Training large models still relies on general-purpose frameworks such as Megatron-LM, whose generality tax constrains scenario-specific optimization and adds runtime overhead throu…