This research presents Hydragen, a hardware-aware model that improves the efficiency of transformer-based large language models (LLMs) working with shared prefixes. It is common for LLMs to perform inferences on…
Continue readingThe paper explores the benefits of transformer-based models’ ability to learn in context from unstructured data during linear regression tasks. It conducts experiments to study the architecture of transformers and…
Continue readingThe paper outlines an approach for the ‘Arabic AI Tasks Evaluation (ArAiEval) Shared Task 2023’, focusing on detection of disinformation and persuasion techniques. Using transformer-based models fine-tuned on Arabic language,…
Continue readingThis paper presents the approach for the ‘Arabic AI Tasks Evaluation (ArAiEval) Shared Task 2023’, focusing on persuasion technique detection and disinformation detection. The authors experiment with several transformer-based models…
Continue readingThe article explores the use of federated learning in electricity load forecasting. The authors propose a novel transformer-based deep learning approach that improves data privacy by training models locally on…
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