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DisCo is a research agent that distills operational knowledge from GitHub repositories into reusable skills, significantly improving autonomous ML research performance across benchmarks like MLE-bench.
This paper introduces Pre-Flight, an open-source benchmark of 300 multiple choice questions designed to evaluate large language models on aviation operational knowledge, covering international regulations and ground operations. Results show even the best models in 2026 score 82.7%, significantly below the expert reference of ~95%, highlighting a persistent reliability gap.
Introduces Teach VLM, a model that extracts step-by-step operational knowledge from mobile screen demonstrations, and the Teach-and-Repeat paradigm that uses this knowledge to guide GUI agents, achieving state-of-the-art performance on a new benchmark.