CLAP: Learning Transferable Binary Code Representations with Natural Language Supervision

Author:

Wang Hao1ORCID,Gao Zeyu1ORCID,Zhang Chao1ORCID,Sha Zihan2ORCID,Sun Mingyang3ORCID,Zhou Yuchen4ORCID,Zhu Wenyu1ORCID,Sun Wenju5ORCID,Qiu Han1ORCID,Xiao Xi5ORCID

Affiliation:

1. Tsinghua University, Beijing, China

2. Information Engineering University, Zhengzhou, China

3. University of Electronic Science and Technology of China, Chengdu, China

4. Beijing University of Technology, Beijing, China

5. Tsinghua University, Shenzhen, China

Publisher

ACM

Reference76 articles.

1. Practical Binary Code Similarity Detection with BERT-based Transferable Similarity Learning

2. Flamingo: a visual language model for few-shot learning;Alayrac Jean-Baptiste;Advances in Neural Information Processing Systems,2022

3. Sebastian Borgeaud Arthur Mensch Jordan Hoffmann Trevor Cai Eliza Rutherford Katie Millican George van den Driessche Jean-Baptiste Lespiau Bogdan Damoc Aidan Clark Diego de Las Casas Aurelia Guy Jacob Menick Roman Ring Tom Hennigan Saffron Huang Loren Maggiore Chris Jones Albin Cassirer Andy Brock Michela Paganini Geoffrey Irving Oriol Vinyals Simon Osindero Karen Simonyan Jack W. Rae Erich Elsen and Laurent Sifre. 2021. Improving Language Models by Retrieving from Trillions of Tokens. arxiv:2112.04426.

4. Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell Sandhini Agarwal Ariel Herbert-Voss Gretchen Krueger Tom Henighan Rewon Child Aditya Ramesh Daniel M. Ziegler Jeffrey Wu Clemens Winter Christopher Hesse Mark Chen Eric Sigler Mateusz Litwin Scott Gray Benjamin Chess Jack Clark Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever and Dario Amodei. 2020. Language Models Are Few-Shot Learners. arxiv:2005.14165.

5. Canonical. 2023. Ubuntu: Enterprise Open Source and Linux. https://ubuntu.com/ Accessed: 2023-06-01

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