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cs.CL2024
MobileQuant: Mobile-friendly Quantization for On-device Language Models
Fuwen Tan, Royson Lee, Łukasz Dudziak +5
Large language models (LLMs) have revolutionized language processing, delivering outstanding results across multiple applications. However, deploying LLMs on edge devices poses sev…
cs.CL2024
Linear-Complexity Self-Supervised Learning for Speech Processing
Shucong Zhang, Titouan Parcollet, Rogier van Dalen +1
Self-supervised learning (SSL) models usually require weeks of pre-training with dozens of high-end GPUs. These models typically have a multi-headed self-attention (MHSA) context e…