Accurate stock market predictions following earnings reports are crucial for investors.
Traditional methods, particularly classical machine learning models, struggle with these …

Pretrained large language models (LLMs) have revolutionized natural language processing
(NLP) tasks such as summarization, question answering, and translation. However, LLMs …

Existing pruning techniques for large language models (LLMs) targeting domain-specific
applications typically follow a two-stage process: pruning the pretrained general-purpose …

Graph neural networks (GNNs) are powerful machine learning models designed to handle
irregularly structured data. However, their generic design often proves inadequate for …

The transformative impact of large language models (LLMs) like LLaMA and GPT on natural
language processing is countered by their prohibitive computational demands. Pruning has …

Managing systems and network policies for largescale organizations is challenging for
business process automation. Although Policy-as-code (PAC) platforms can ease the task of …