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University of Illinois Urbana-Champaign
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Agents can boost their task completion rates by over 20% simply by grounding their actions in observed context rather than assumptions.
Domain-specific fine-tuning can induce "agentic collapse" in LLMs, but a surprisingly small amount of agentic data from *another* domain can bring those general tool-use skills roaring back.
