Exploring and Characterizing Large Language Models for Embedded System Development and Debugging-Reference-Cited by-同舟云学术

Exploring and Characterizing Large Language Models for Embedded System Development and Debugging

Published:2024-05-11 Issue: Volume: Page:1-9
ISSN:
Container-title:Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
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Author:

Englhardt Zachary¹^ORCID,Li Richard¹^ORCID,Nissanka Dilini¹^ORCID,Zhang Zhihan¹^ORCID,Narayanswamy Girish²^ORCID,Breda Joseph¹^ORCID,Liu Xin¹^ORCID,Patel Shwetak³^ORCID,Iyer Vikram¹^ORCID

Affiliation:

1. Paul G. Allen School of Computer Science & Engineering, University of Washington, United States

2. Department of Electrical and Computer Engineering, University of Washington, United States

3. Paul G. Allen School of Computer Science & Engineering, University of Washington, United States and Department of Electrical and Computer Engineering, University of Washington, USA

Funder

Washington NASA Space Grant Consortium

Amazon Web Services

Google

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613905.3650764

Reference58 articles.

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4. Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020), 1877–1901.

5. Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, 2023. Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv preprint arXiv:2303.12712 (2023).

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