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Persuasion in LLM networks is not just about who speaks, but how the topology and exposure shape stance shifts, revealing a complex interplay of influence that traditional analysis overlooks.
Real-world deployment of LLM-based agents reveals critical safety and reliability challenges that traditional benchmarks overlook.
Dependency-controlled context and explicit evidence sufficiency criteria are key to preventing premature stopping and improving the consistency of enterprise research outputs.
