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Efficient evaluation methods can drastically alter the conclusions drawn about model behavior, revealing hidden vulnerabilities in AI benchmarking.
Auditable financial chart QA is now achievable on-premise without sacrificing accuracy, revealing critical insights into model failures and trustworthiness.