32 citations · 92 across the 21 of their papers we have counts for
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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.CL2026
Margins, Not Windows: Training-Free Per-Step Lossy Speculative Decoding
Oszkár Urbán, Young D. Kwon, Stylianos I. Venieris +1
Speculative decoding accelerates LLM inference by drafting candidate tokens and verifying them in parallel. Tree-attention drafters such as EAGLE-3 are widely adopted, yet typicall…