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This work studies continual enterprise world model discovery, where an agent starts without knowledge of these business rules and discovers them by interacting with records and observing the outcomes, and builds a world model, which it revises as the rules change.
A VLM-as-a-Judge metric for SVG generation, validated through human correlation studies, and an evaluation of frontier VLMs reveals significant performance gaps, positioning VectorGym as a rigorous framework for advancing visual code generation.
PiSAs (Privacy in Shared Agentic systems), a benchmark for assessing unintentional leaks with dual CI annotations, enables direct measurement of cross-user spillage across agentic system components and interfaces, such as outputs, inter-agent communication, and memory.
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