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University of Maryland College
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Reasoning models may boost performance but often sacrifice critical alignment behaviors, revealing a hidden trade-off in AI safety.
Instead of imitating reflections, LLM agents can be trained to reason about action quality by rewarding correct judgments between alternative actions, leading to improved performance and generalization.
