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Agents in CivBench under-monitor strategic states and frequently fail to act on their own planning commitments, revealing critical gaps in tool-mediated decision-making.
AI agents can handle the engineering aspects of research but fall short in addressing the core research questions, leading to outright rejections from experts.
Fixed-budget evaluations can significantly underestimate the capabilities of advanced language models, with larger token budgets unlocking their true potential across diverse tasks.