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Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires interpreting specialized interfaces, manipulating scientific objects, and producing verifiable results. We thus introduce OSWorld-Science, a benchmark and evaluation en...
Noise-Aware Verbal Confidence CAlibration Rules are proposed to provide a principled foundation for resolving overconfidence under noise and NOVA, a noise-aware calibration framework that synthesizes supervision from ~2K HotpotQA examples guided by these rules.
This study provides new mechanistic insights into how LLMs internalize OOD challenges, and designs Sparsity-Guided Curriculum In-Context Learning (SG-ICL), a strategy that explicitly uses representation sparsity to schedule few-shot demonstrations, leading to considerable performance enhancements.
Occamy-1.0, a cost-efficient co-work model obtained by further training the post-trained Qwen3.6-35B-A3B checkpoint, is presented and placed at the low-cost knee of the observed cost--performance Pareto frontier.
This work recast five text-to-SQL datasets as retrieval tasks at both table and column granularity, covering realistic and enterprise-scale schemas under two document representations, and proposes corpus-adaptive fine-tuning, establishing schema linking as a standalone retrieval task and lightweight, label-free corpus...
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