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This work introduces \textsc{ArchOR], an archetype-centric skill agent that builds on \textsc{OptSkills} by adding two retrieval-focused modules, and refines the ordering of cached skill representations through a low-rank prototype residual.
In this report, we introduce Sage-A1.5, a 35B Mixture-of-Experts agentic model that builds on A1 to advance long-horizon problem solving through adaptive capability composition. Compared with A1, Sage-A1.5 learns not only to solve individual tasks, but also to organize work and revise its approach during execution. Sag...
UnicDocVLM is proposed, an end-to-end framework that unifies OCR and visual RAG within a single vision-language model: the model first generates a structured parse of retrieved pages, then activates question-relevant evidence from the parse to support grounded reasoning and answering.
UnicDocVLM is proposed, an end-to-end framework that unifies OCR and visual RAG within a single vision-language model: the model first generates a structured parse of retrieved pages, then activates question-relevant evidence from the parse to support grounded reasoning and answering.
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