SWE-Interact shows frontier models solve roughly 25% of multi-turn interactive coding tasks versus 50% on single-turn baselines.
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LLM agents overcommit on non-complete tasks at 41.7% unless given explicit support-state categories, which raise typed deferral accuracy to 91.7%.
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SWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding Sessions
SWE-Interact shows frontier models solve roughly 25% of multi-turn interactive coding tasks versus 50% on single-turn baselines.
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Don't Start What You Can't Finish: A Counterfactual Audit of Support-State Triage in LLM Agents
LLM agents overcommit on non-complete tasks at 41.7% unless given explicit support-state categories, which raise typed deferral accuracy to 91.7%.