U-Net Encapsulated Transformer for Reducing Dimensionality in Training Large Language Models

ACM Transactions on Intelligent Systems and Technology, Journal Year: 2025, Volume and Issue: unknown

Published: May 13, 2025

Training language models from scratch presents a critical challenge in Natural Language Processing (NLP), primarily due to the computational demands of pre-trained Large Models, which are predominantly trained on English corpora using extensive resources. While offering viable solutions, existing alternatives still rely heavily high-performance hardware. This work introduces different approach reducing algorithmic complexity Transformer-based architectures through U-Net Encapsulated Transformer (UET), applies dimensionality reduction token embeddings. The UET architecture enables development with significantly reduced parameter sizes for given set hyperparameters. Alternatively, it allows researchers design comparable size but substantially greater number blocks, enhancing model depth and potential capacity. study also outlines practical methodologies training resource-constrained environments. Experimental results illustrate achieving reasonable performance under conditions, highlighting its promise as an accessible alternative development. could broaden accessibility NLP research, empowering hardware constraints contribute

Language: Английский

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How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About It

Published: April 24, 2025

Language: Английский

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The Need to Focus More on Climate Change Communication and Incorporate More Systems Approaches

Journal of Health Communication, Journal Year: 2024, Volume and Issue: 29(sup1), P. 1 - 10

Published: June 3, 2024

Society is at an inflection point-both in terms of climate change and the amount data computational resources currently available. Climate has been a catastrophe slow motion with relationships between human activity, change, resulting effects forming complex system. However, to date, there general lack urgent responses from leaders public, despite warnings scientific community about consequences what can be done mitigate it. Further, misinformation disinformation abound. A major problem that not enough focus on communication field. Since itself involves systems (e.g. information users, itself, communications channels), need for more approaches change. Utilizing really understand anticipate how may distributed received before even occurred adjust accordingly lead proactive precision communication. The time come identify develop effective, tailored, precise

Language: Английский

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Navigating Generative AI Tools in the Classroom Through a Lens of Equity and Accessibility

Journal of Political Science Education, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 13

Published: Nov. 8, 2024

The open release of ChatGPT in late 2022 sent the world education into a frenzy. Popular media outlets both sang praises generative AI and also posed questions about what meant for future teaching learning. In year that has followed, we have seen broad range strategies managing on campuses ranging from total bans to embrace encouragement. As such, many instructors feel lost unguided how approach their classrooms. response lack clarity direction or alternatives, an increasing number administrators are considering tools. this article, offer set considerations landscape classroom work settings followed by three models (high, medium, low use) can use small, large classrooms navigate higher setting.

Language: Английский

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Applications of generative artificial intelligence to influence climate change decisions

npj Climate Action, Journal Year: 2024, Volume and Issue: 3(1)

Published: Dec. 21, 2024

Language: Английский

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