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Entropic Advantage Policy Optimization (EAPO) is introduced, an entropy-guided credit assignment method that treats success and failure asymmetrically and promotes more effective exploration, broadening problem coverage and generating more diverse candidate answers.
FlyBy is introduced, a selective querying framework, and 4B and 8B variants are trained to reason first, diagnose what remains unresolved, and, at a knowledge bottleneck, query stronger models whose parametric knowledge extends beyond its own.
A trajectory-aware evolutionary search method, T-MAP, which leverages execution trajectories to guide the discovery of adversarial prompts and enables the automatic generation of attacks that not only bypass safety guardrails but also reliably realize harmful objectives through actual tool interactions.
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