Ziqi Zhang
@ZiqiCharlesCS Postdoc at @UofIllinois. Graduated from @PKU1898. Software engineering, AI, and computer security.
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Intern position at @brave : brave.com/careers/ My team is looking for strong students interested in private, secure and trustworthy ML. Feel free to email me with the subject line "Brave Internship 2025" and highlight your 3 most significant publications on these topics.
How to leverage the white-box info (i.e. source code) for fuzzing compilers? Check out our work “WhiteFox 🦊: White-Box Compiler Fuzzing Empowered by Large Language Models” at OOPSLA 2024! w/ @yinlin_deng, @lry89757, JIayi Yao, @JiaweiLiu_, @Reyhaneh, and @LingmingZhang (1/N)
I'm on the way to USENIX Security'24. We will present one paper about privacy-preserving app authentication. I'm also happy to discuss TEE-based AI security and other AI-related security topics. If you're interested, please get in touch with me! #usenix #USESEC2024
😺Agentless! Do we need complicated agents to solve real-world SE tasks? No!
Introducing OpenAutoCoder-Agentless😺: A simple agentless solution solves 27.3% GitHub issues on SWE-bench Lite with ~$0.34 each, outperforming all open-source AI SW agents! It's fully open-source, try it out: 🧑💻github.com/OpenAutoCoder/… 📝huggingface.co/papers/2407.01…
An elegant idea for MoE!
🚀 Introducing “XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts” at #ACL2024 XFT is a novel training scheme for instruction tuning to achieve upcycled MoE performance with dense-model compute in inference arxiv.org/abs/2404.15247
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Ting Su
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CC
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Yiling Lou
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Pei Liu
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Chengpeng Wang
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Danning Xie | OpenToWork
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