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Lihan

SJTU-furrina

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reacted to YerbaPage's post with 🔥 about 1 month ago

Latest work on SWE-Bench 🐛 Our two new papers from the SJTU & Huawei: Powered by DeepSeek-V3, we've achieved a new SOTA on the SWE-Bench benchmark! We introduce two innovative approaches: ⚔️ SWE-Debate: AI agents compete and "debate" to generate the best code fix. 🧠 SWE-Exp: An AI agent learns from past repair "experience" to solve new issues more efficiently. 👇 Explore the future of software development: SWE-Debate 📄 Paper: https://arxiv.org/abs/2507.23348 💻 Code: https://github.com/YerbaPage/SWE-Debate SWE-Exp 📄 Paper: https://arxiv.org/abs/2507.23361 💻 Code: https://github.com/YerbaPage/SWE-Exp

upvoted a paper 3 months ago

SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution

reacted to YerbaPage's post with 👀 4 months ago

Latest work on SWE-Bench 🐛 Our two new papers from the SJTU & Huawei: Powered by DeepSeek-V3, we've achieved a new SOTA on the SWE-Bench benchmark! We introduce two innovative approaches: ⚔️ SWE-Debate: AI agents compete and "debate" to generate the best code fix. 🧠 SWE-Exp: An AI agent learns from past repair "experience" to solve new issues more efficiently. 👇 Explore the future of software development: SWE-Debate 📄 Paper: https://arxiv.org/abs/2507.23348 💻 Code: https://github.com/YerbaPage/SWE-Debate SWE-Exp 📄 Paper: https://arxiv.org/abs/2507.23361 💻 Code: https://github.com/YerbaPage/SWE-Exp

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