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RT @yifannnwu: Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions. Coding agents are often benchm…
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RT @yifannnwu: Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions. Coding agents are often benchm…
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"text": "RT @yifannnwu: Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions.\n\nCoding agents are often benchm…",
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"text": "Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions.\n\nCoding agents are often benchmarked like exam-takers: given the full spec up front, then graded on the final code. But real coding help is a conversation — users clarify goals, add constraints, and correct course along the way.\n\nSWE-Together turns real coding work into a reproducible, verifiable benchmark: 109 repo-level tasks curated from 11,260 recorded sessions, replayed with a reactive LLM user simulator that preserves the original user’s intent.\n\nWe evaluate agents as collaborators, not just patch generators: final pass rate and how many user interventions were needed to get there.\n\nIn this evaluation snapshot, claude-opus-4.8 currently leads among the 7 agents we tested — achieving the highest pass rate while requiring the fewest user interventions.\n\n📄 Paper: https://t.co/Zp5BSPpLTJ\n💻 Code: https://t.co/NPgxCMLdHi\n🌐 Website: https://t.co/BK50zRGReE",
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