Compressing code generation language models on CPUs: Using Group Lasso pruning and post-training quantization

Code generation models have become more popular recently, due to the fact that they assist developers in writing code in a more productive manner. While these large models deliver impressive performance, they require significant computational resources and memory, making them difficult to deploy and expensive to train. Additionally, their large...

How can large language models and prompt engineering be leveraged in Computer Science education?: Systematic literature review

In recent years, significant progress has been made in the field of natural language processing (NLP) through the development of large language models (LLMs) like BERT and ChatGPT. These models have showcased remarkable abilities across a range of NLP tasks. However, effectively harnessing their potential requires meticulous prompt engineering...

Development and Reuse of Engineering Automation

Increasingly engineers in, for example, Aerospace Engineering create software to support their daily engineering activities. This is referred to as Engineering Automation. A prime example of Engineering Automation is Knowledge Based Engineering. It is desirable to reuse and share this software, rather than to discard it soon after its creation....