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Ignoring prompt knowledge is a critical security flaw, as LLMs can covertly transmit hidden messages through their deterministic sampling processes.
Refusals from LLMs can be transformed into supportive communications that not only prevent harm but also guide users toward helpful resources.
LLM-powered agents can autonomously generate fuzz harnesses for Java libraries, outperforming existing automated approaches and even uncovering bugs in well-fuzzed code.
