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BENCHCOMPASS is introduced, a payment-domain benchmark whose construction pipeline builds scenario-grounded tasks from typed evidence packs, applies LLM-based quality checks, creates task-input attack variants, and reserves final item admission for domain experts.
Agents can now effectively collaborate in multi-robot systems even when facing unpredictable computational delays, leading to improved learning and control performance.
Novel high-order control barrier functions enable explicit safety control in nonlinear systems, ensuring stabilization without compromising safety.
