3 papers
cs.LG2026
DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training
Dong Wang, Wenwu Tang, Yun Cheng +1
Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank pre-training, which factorizes…
cs.LG2026
GRAIL: Post-hoc Compensation by Linear Reconstruction for Compressed Networks
Wenwu Tang, Dong Wang, Lothar Thiele +1
Structured deep model compression methods are hardware-friendly and substantially reduce memory and inference costs. However, under aggressive compression, the resulting accuracy d…
eess.IV2025
Towards 3D Semantic Image Synthesis for Medical Imaging
Wenwu Tang, Khaled Seyam, Bin Yang
In the medical domain, acquiring large datasets is challenging due to both accessibility issues and stringent privacy regulations. Consequently, data availability and privacy prote…