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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…