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cs.CL2025
TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices
Mingxue Xu, Yao Lei Xu, Danilo P. Mandic
Small Language Models (SLMs, or on-device LMs) have significantly fewer parameters than Large Language Models (LLMs). They are typically deployed on low-end devices, like mobile ph…
cs.CL2024
Geometry is All You Need: A Unified Taxonomy of Matrix and Tensor Factorization for Compression of Generative Language Models
Mingxue Xu, Sadia Sharmin, Danilo P. Mandic
Matrix and tensor-guided parametrization for Natural Language Processing (NLP) models is fundamentally useful for the improvement of the model's systematic efficiency. However, the…
cs.CL2023★ 6 cited
TensorGPT: Efficient Compression of Large Language Models based on Tensor-Train Decomposition
Mingxue Xu, Yao Lei Xu, Danilo P. Mandic
High-dimensional token embeddings underpin Large Language Models (LLMs), as they can capture subtle semantic information and significantly enhance the modelling of complex language…