Binding Drift in Multi-Step Tool-Augmented Agents
A new preprint formalizes 'binding drift' in tool-augmented language-model agents, where entity bindings that are correct at step 1 can silently become incorrect in later steps, distinct from simple error propagation. In a controlled testbed, the commonly suggested 'entity lock' fix actually amplifies wrong actions by 3x, while a lightweight LLM-based re-verifier reduces wrong actions by 79%, nearly matching an oracle upper bound.
Why it matters: This work identifies a previously underappreciated failure mode in multi-step tool-augmented agents and demonstrates a practical mitigation, with direct implications for the reliability of such systems.
Full story at: arXiv Software Engineering ↗