OmegaUse-OfficeVal: Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding
Researchers released OmegaUse-OfficeVal, a benchmark testing LLM agents on complex office workflows with cost efficiency metrics.
- New benchmark focuses on long-horizon office tasks with economic grounding.
- Dataset features 100 real-world tasks averaging 2.3 hours of human work.
- Evaluation includes cost-effectiveness metrics alongside task completion.
The new OmegaUse-OfficeVal benchmark addresses the need to evaluate large language model agents on realistic, long-horizon office workflows. Unlike previous tests, this framework incorporates economic grounding to assess whether agents can complete tasks at a reasonable cost.
The dataset includes 100 distinct tasks derived from real office requests by practitioners. These tasks were adapted using a privacy-preserving process to ensure they reflect genuine professional needs without compromising sensitive data.
On average, completing these tasks requires approximately 2.32 hours of human labor. This metric allows researchers to compare agent performance not just on accuracy, but on the economic value and time savings they provide over manual work.
Provides a rigorous standard to test agent capabilities on realistic, multi-step workflows.
Offers a framework to assess if AI agents can deliver actual economic value in office settings.
Helps evaluate the commercial viability and efficiency of agent-based startups.
- Economic grounding
- Evaluating AI performance based on cost-effectiveness and economic value relative to human labor.
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