1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs
Ling Team, Binwei Zeng, Chao Huang +71
In this technical report, we tackle the challenges of training large-scale Mixture of Experts (MoE) models, focusing on overcoming cost inefficiency and resource limitations preval…
cs.CV2024
Attention-Guided Perturbation Network for Industrial Anomaly Detection
Tingfeng Huang, Weijia Kong, Huan Liu +4
In unsupervised image anomaly detection, reconstruction-based methods learn normal patterns for data reconstruction, but often undesirably reconstruct anomalous regions at inferenc…