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Agent Development Kits vary dramatically in usability, with some enabling agents to outperform general-purpose coding tools at a fraction of the cost.
Explicitly invoking external image tools in vision-language models dramatically reduces jailbreak success rates, even when the tool's output is overridden or unsafe.
MLLMs still struggle to reason about everyday situations when they require identifying and using visual clues, despite excelling at tasks relying on pre-existing knowledge.
