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## Abstract 本文：TitanFuzz Task: use LLM to fuzz DL librarires Method: use both generative and infilling LLMs(e.g., Codex, InCoder) 实验： 对象：Tensorflow, P 阅读全文
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## Abstract 背景： 挑战： 1. need valid input domain of each API function 2. hard to trigger new behavior 本文：SkipFuzz 任务: fuzz machine learning libraries us 阅读全文
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## Abstract 本文：ConFL Task: Fuzz Deep Learning Libraries using Constraint-guided fuzzer Method: Constraint-guided fuzzer + grouping 实验： 对象：Tensorflow(M 阅读全文
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## Abstract 本文：DeFuzz Task: guided directed fuzzing Method: pre-trained BiLSTM to identify the potentially vulnerable functions, directed fuzzing 实验： 阅读全文
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## Abstract 背景：在最近一项bug study中，high-level IR的优化导致44.92%的bug(Q?) 本文: HirGen Github: https://github.com/haoyang9804/HirGen Task: fuzzing the optimizatio 阅读全文
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## Abstract 本文：DRFuzz Task: find the regression faults between versions of a DL system Method: 1. a diversity-oriented test criterion to explore as ma 阅读全文
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## Abstract 背景：每个深度学习库 API 都可以抽象为处理张量/向量的函数(each DL library API can be abstracted into a function processing tensors/vectors)，可用来差分测试 本文：∇Fuzz Task: A 阅读全文
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## Abstract 本文: DPFuzz Github: https://github.com/Tizpaz/DPFuzz Task: Differential performance analysis with input groups， provide an explanation for 阅读全文