Researchers from China Introduced a Novel Compression Paradigm called Retrieval-based Knowledge Transfer (RetriKT): Revolutionizing the Deployment of Large-Scale Pre-Trained Language Models in Real-World Applications

Natural language processing (NLP) applications have shown remarkable performance using pre-trained language models (PLMs), including BERT/RoBERTa. However, because of their enormous complexity, these models—which generally have hundreds of millions of parameters—present a significant difficulty for researchers. Thus, large-scale pre-trained language models (PLMs) have not yet reached their full potential. Many model compression strategies, including weight […]

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