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Fuzzing, a widely-used technique for bug detection, has seen advancements through Large Language Models (LLMs).
A systematic review of fuzzing techniques
Chen Chen, Baojiang Cui, Jinxin Ma, Runpu Wu, Jianchao Guo, and Wenqian Liu. 2018 · 2018
Earlier work this paper cites.
Hallucinations in neural machine translation
Katherine Lee, Orhan Firat, Ashish Agarwal, Clara Fannjiang, and David Sussillo. 2018 · 2018
Earlier work this paper cites.
Fuzzing: State of the art
Hongliang Liang, Xiaoxiao Pei, Xiaodong Jia, Wuwei Shen, and Jian Zhang. 2018 · 2018
Earlier work this paper cites.
Object hallucination in image captioning
Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, and Kate Saenko. 2018 · 2018
Earlier work this paper cites.
CVE-2021-40523
MITRE. 2021 · 2021
Earlier work this paper cites.
{ \{ KSG } \} : Augmenting Kernel Fuzzing with System Call Specification Generation. In 2022 USENIX Annual Technical Conference (USENIX ATC 22) . 351–366
Hao Sun, Yuheng Shen, Jianzhong Liu, Yiru Xu, and Yu Jiang. 2022 · 2022
Earlier work this paper cites.
Large Language Models for Fuzzing Parsers (Registered Report). In Proceedings of the 2nd International Fuzzing Workshop . 31–38
Joshua Ackerman and George Cybenko. 2023 · 2023
Earlier work this paper cites.
A survey on evaluation of large language models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al · 2023
Earlier work this paper cites.
Effective test generation using pre-trained large language models and mutation testing
Arghavan Moradi Dakhel, Amin Nikanjam, Vahid Majdinasab, Foutse Khomh, and Michel C Desmarais. 2023 · 2023
Earlier work this paper cites.
Large Language Model Powered Test Case Generation for Software Applications
Victor Dantas. 2023 · 2023
Earlier work this paper cites.
Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects
Muhammad Usman Hadi, Rizwan Qureshi, Abbas Shah, Muhammad Irfan, Anas Zafar, Muhammad Bilal Shaikh, Naveed Akhtar, Jia Wu, Seyedali Mirjalili, et al · 2023
Earlier work this paper cites.
Large language models for software engineering: A systematic literature review
Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John Grundy, and Haoyu Wang. 2023 · 2023
Earlier work this paper cites.
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
Cited alongside, same era.
Automated Bug Generation in the era of Large Language Models
Ali Reza Ibrahimzada, Yang Chen, Ryan Rong, and Reyhaneh Jabbarvand. 2023 · 2023
Cited alongside, same era.
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach
Zhenlan Ji, Pingchuan Ma, Zongjie Li, and Shuai Wang. 2023 · 2023
Cited alongside, same era.
Challenges and applications of large language models
Jean Kaddour, Joshua Harris, Maximilian Mozes, Herbie Bradley, Roberta Raileanu, and Robert McHardy. 2023 · 2023
Cited alongside, same era.
Universal fuzzing via large language models
Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, and Lingming Zhang. 2023 · 2023
Later among the works it cites.
White-box compiler fuzzing empowered by large language models
Chenyuan Yang, Yinlin Deng, Runyu Lu, Jiayi Yao, Jiawei Liu, Reyhaneh Jabbarvand, and Lingming Zhang. 2023a · 2023
Later among the works it cites.
KernelGPT: Enhanced Kernel Fuzzing via Large Language Models
Chenyuan Yang, Zijie Zhao, and Lingming Zhang. 2023b · 2023
Later among the works it cites.
Understanding large language model based fuzz driver generation
Cen Zhang, Mingqiang Bai, Yaowen Zheng, Yeting Li, Xiaofei Xie, Yuekang Li, Wei Ma, Limin Sun, and Yang Liu. 2023 · 2023
Later among the works it cites.
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Siva Kesava Reddy Kakarla and Ryan Beckett. 2023 · 2023
Cited alongside, same era.
Large language models (LLMs) for natural language processing (NLP) of oil and gas drilling data. In SPE Annual Technical Conference and Exhibition? SPE, D021S012R004
Prateek Kumar and Sanjay Kathuria. 2023 · 2023
Cited alongside, same era.
Large Language Model-Aware In-Context Learning for Code Generation
Jia Li, Ge Li, Chongyang Tao, Huangzhao Zhang, Fang Liu, and Zhi Jin. 2023a · 2023
Cited alongside, same era.
Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 14–26
Tsz-On Li, Wenxi Zong, Yibo Wang, Haoye Tian, Ying Wang, Shing-Chi Cheung, and Jeff Kramer. 2023b · 2023
Cited alongside, same era.
Evaluating large language models for radiology natural language processing
Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, Peng Shu, et al · 2023
Cited alongside, same era.
Prompt Fuzzing for Fuzz Driver Generation
Yunlong Lyu, Yuxuan Xie, Peng Chen, and Hao Chen. 2023 · 2023
Cited alongside, same era.
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, and Omer Levy. 2023 · 2023
Cited alongside, same era.
Utilizing Large Language Models for Fuzzing: A Novel Deep Learning Approach to Seed Generation
Elwin Tamminga, Bouwko van der Meijs, and Ultraware Stjepan Picek. 2023 · 2023
Cited alongside, same era.
Large Language Model guided Protocol Fuzzing. In Proceedings of the 31st Annual Network and Distributed System Security Symposium (NDSS)
Ruijie Meng, Martin Mirchev, Marcel Böhme, and Abhik Roychoudhury. 2024 · 2024
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2023 · 2026
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2023 · 2026
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2023 · 2026
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MonetDB Website
MonetDB B.V. 2023 · 2026
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DuckDB. 2023 · 2026
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ClickHouse Website
ClickHouse Inc. 2023 · 2026
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AI-Powered Fuzzing: Breaking the Bug Hunting Barrier
Google Open Source Security Team. [n. d.] · 2026
Closest in time.