This academic article delves into the potential and challenges of task-oriented and semantic communications for next-generation (NextG) networks. It discusses the integration of multi-task learning, using deep neural networks for…
Continue readingThis research investigates deception, especially lies of omission, using Natural Language Processing (NLP) techniques. A dataset of 876,784 samples was curated by merging a large-scale fake news dataset and scraped…
Continue readingThe article discusses the application of multi-task learning (MTL) in end-to-end speech translation (ST). It investigates the consistency between different tasks in MTL and their effect on the ST task….
Continue readingThis paper presents a new approach to optimizing cascade ranking systems, which are widely used in online advertising and recommendation systems. The authors propose the Adaptive Neural Ranking Framework (ARF),…
Continue readingThe study proposes a new method, Imprecise Bayesian Continual Learning (IBCL), to address task trade-offs in continual learning. Unlike existing algorithms, IBCL does not require additional training overhead to generate…
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