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Found 5 papers, 0 papers with code
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
To our best knowledge, we are the first work that achieves almost lossless quantization performance for LLMs under a data-independent setting and our algorithm runs over 10 times faster than the data-dependent methods.
E-Sparse: Boosting the Large Language Model Inference through Entropy-based N:M Sparsity
Traditional pruning methods are known to be challenging to work in Large Language Models (LLMs) for Generative AI because of their unaffordable training process and large computational demands.
MKQ-BERT: Quantized BERT with 4-bits Weights and Activations
In this work, we propose MKQ-BERT, which further improves the compression level and uses 4-bits for quantization.
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
Spatial Sparse subspace clustering for Compressive Spectral imaging
This paper aims at developing a clustering approach with spectral images directly from CASSI compressive measurements.
