The Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks-Reference-Cited by-同舟云学术

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The Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks

Published:2024-04-14 Issue: Volume: Page:35-39
ISSN:
Container-title:Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering
language:
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Author:

Venkatesh Ashwin Prasad Shivarpatna¹^ORCID,Sabu Samkutty²^ORCID,Mir Amir M.³^ORCID,Reis Sofia⁴^ORCID,Bodden Eric⁵^ORCID

Affiliation:

1. Heinz Nixdorf Institut, Paderborn University, Paderborn, Germany

2. Paderborn University, Paderborn, DC, Germany

3. Delft University of Technology, Delft, Netherlands

4. INESC-ID and IST, University of Lisbon, Lisbon, Portugal

5. Heinz Nixdorf Institut & Fraunhofer IEM, Paderborn University, Paderborn, Germany

Funder

Ministry of Culture and Science of the State of North Rhine-Westphalia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650105.3652288

Reference24 articles.

1. [n. d.]. Hugging Face - The AI Community Building the Future. https://huggingface.co/.

2. [n. d.]. Langchain-Ai/Langchain: Building Applications with LLMs through Composability. https://github.com/langchain-ai/langchain.

3. [n. d.]. Ollama. https://ollama.ai.

4. Typilus: neural type hints

5. Banghao Chen Zhaofeng Zhang Nicolas Langrené and Shengxin Zhu. 2023. Unleashing the Potential of Prompt Engineering in Large Language Models: A Comprehensive Review. arXiv:2310.14735 [cs]

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