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OmegaUse-OfficeVal is introduced, a benchmark for evaluating LLM agents on long-horizon office-suite tasks with task-level economic grounding, and code-based verifiers from fine-grained rubrics are developed to support stable evaluation.
While deep learning models, particularly transformer-based architectures, have shown impressive performance in time series forecasting, the application of retrieval-augmented generation (RAG) in this domain remains limited. Since RAG has proven effective in enhancing the capabilities of large language models by incorpo...
OmegaUse-SOP is introduced, a human-in-the-loop SOP Engineering system for transforming human demonstrations of professional computer use into reusable SOP skills for GUI agents, and the results suggest that OmegaUse-SOP can improve GUI-agent reliability on professional SOP tasks.
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