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cs.LG2026
On the Interaction Between Model Compression and Test-Time Adaptation
Francesco Corti, Dong Wang, Young D. Kwon +2
Deep neural networks deployed in the wild must be both efficient and adaptable, requiring model compression and test-time adaptation (TTA). While both are well studied in isolation…
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…