AI RESEARCH
To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents
arXiv CS.AI
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ArXi:2605.18882v1 Announce Type: cross LLM agents exhibit a consistent tendency to over-call, invoking tools even in situations where none is needed. On the When2Call benchmark, six models from three families show high call accuracy but much lower no-call accuracy, leaving overall accuracy in the 55%-70% range. We trace this to an Intrinsic Bias Hypothesis (IBH): the call/no-call decision mapping carries an activation-independent call offset, so the model favors call even at activation parity.