Steven Xia @steven_xia_
PhD Student @illinoisCDS studying SE \\ Undergrad @eceuoft 2T1 steven.cs.illinois.edu Champaign-Urbana, Illinois Joined February 2013-
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We're releasing a new iteration of SWE-bench, in collaboration with the original authors, to more reliably evaluate AI models on their ability to solve real-world software issues. openai.com/index/introduc…
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
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…
Magicoder: Source Code Is All You Need paper page: huggingface.co/papers/2312.02… introduce Magicoder, a series of fully open-source (code, weights, and data) Large Language Models (LLMs) for code that significantly closes the gap with top code models while having no more than 7B…
In the past 6-mon release of HumanEval+ we have been improving its toolchain usability and dataset quality from v0.1.0 to v0.1.7 releases. 🔥 Now we release MBPP+, a new benchmark in EvalPlus v0.2.0: tinyurl.com/4pw82wb8 🧵
Introducing the EvalPlus leaderboard! evalplus.github.io/leaderboard.ht… 🔥28 models have been evaluated on coding HumanEval & HumanEval+ 🔥7B CodeLlama outperforms ~16B models e.g. StarCoder&CodeGen 🔥Phind-CodeLlama-34B-v2 and WizardCoder-Python-34B-V1 as open models both beat ChatGPT 🧵
OK now we have @steven_xia_ on his work with @YuxiangWei9 and @LingmingZhang, all of @plfmse. Talking about program repair using large pre-trained language models
We welcome everyone to try out 📚𝐇𝐮𝐦𝐚𝐧𝐄𝐯𝐚𝐥+! A dataset to reflect the "real" correctness of LLM-generated code. Using📚𝐇𝐮𝐦𝐚𝐧𝐄𝐯𝐚𝐥+ is the same as HumanEval. You can easily pip install it and evaluate in our prepared sandbox (optional). github.com/evalplus/evalp…
We welcome everyone to try out 📚𝐇𝐮𝐦𝐚𝐧𝐄𝐯𝐚𝐥+! A dataset to reflect the "real" correctness of LLM-generated code. Using📚𝐇𝐮𝐦𝐚𝐧𝐄𝐯𝐚𝐥+ is the same as HumanEval. You can easily pip install it and evaluate in our prepared sandbox (optional). github.com/evalplus/evalp… https://t.co/yxqWHdBaKZ
🚨 Evaluating LLM-generated code on datasets with just "3 test-cases" is NOT enough! 🚨 We built ✨HumanEval+✨: improving HumanEval with up to thousands of new tests to fully evaluate functional correctness of LLM generated code! @JiaweiLiu_ @YuyaoStarling @LingmingZhang
🚨 Evaluating LLM-generated code on datasets with just "3 test-cases" is NOT enough! 🚨 We built ✨HumanEval+✨: improving HumanEval with up to thousands of new tests to fully evaluate functional correctness of LLM generated code! @JiaweiLiu_ @YuyaoStarling @LingmingZhang https://t.co/qFuzrO9zac
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation Proposes EvalPlus – a code synthesis benchmarking framework to rigorously evaluate the functional correctness of LLM-synthesized code. arxiv.org/abs/2305.01210
GAME WINNER! SERIES WINNER! LET’S. GO. LEAFS. NATION!!!!!!!!!
Today we will present our new work "NNSmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers" @ASPLOSConf at Session 2A (1pm PT). Welcome to join our talk to learn how we build an automated tool for finding 70+ bugs (and more now!) for emerging DL compilers!
🚨LLMs are Zero-Shot Fuzzers! Excited to share our TitanFuzz🤖 work @issta23: #LLMs can be directly applied for both generative and mutative fuzzing, while being fully automated, generalizable, and applicable to domains challenging for traditional fuzzers (such as DL systems)🧵
2. Automated Program Repair in the Era of Large Pre-trained Language Models. Authors: Chunqiu Steven Xia (@steven_xia_), Yuxiang Wei (@YuxiangWei9), Lingming Zhang (@LingmingZhang). Pre-print: arxiv.org/abs/2210.14179
Talia Ringer 💚 @TaliaRinger
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