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No current LLM-based agent can reliably avoid executing unsafe actions when using third-party skills, with a staggering 17% failure rate even in optimal conditions.
Saliency-guided sparse updates, focusing on high-magnitude activations in query and key vectors, unlock significant performance gains in long-context RL, outperforming uniform update strategies.
