Demystifying and Detecting Misuses of Deep Learning APIs-Reference-Cited by-同舟云学术

Demystifying and Detecting Misuses of Deep Learning APIs

Published:2024-04-12 Issue: Volume:35 Page:1-12
ISSN:
Container-title:Proceedings of the IEEE/ACM 46th International Conference on Software Engineering
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Author:

Wei Moshi¹^ORCID,Harzevili Nima Shiri¹^ORCID,Huang Yuekai²^ORCID,Yang Jinqiu³^ORCID,Wang Junjie⁴^ORCID,Wang Song¹^ORCID

Affiliation:

1. York University, Toronto, Canada

2. University of Chinese Academy of Sciences, Beijing, China

3. Concordia University, Montreal, Canada

4. Institute of Software, Chinese Academy of Sciences, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597503.3639177

Reference57 articles.

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2. Understanding Training Efficiency of Deep Learning Recommendation Models at Scale

3. Rachith Aiyappa, Jisun An, Haewoon Kwak, and Yong-Yeol Ahn. 2023. Can we trust the evaluation on ChatGPT? arXiv preprint arXiv:2303.12767 (2023).

4. Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, et al. 2016. Theano: A Python framework for fast computation of mathematical expressions. arXiv e-prints (2016), arXiv-1605.

5. MUBench

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