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Introduces Efficient Operator Search (EOS), a unified differentiable framework that generalizes token reduction methods (pruning, merging, pooling, adaptive reweighting) into a shared operator space, automatically searching for optimal operator compositions under budget constraints. The method achieves competitive results across benchmarks and reveals consistent operator patterns.
Introduces FaraGen, a synthetic data generation system for computer use agents, and Fara-7B, a small but efficient model that outperforms larger counterparts on web task benchmarks. The model is released open-weight on Microsoft Foundry and HuggingFace.