Binding Drift in Multi-Step Tool-Augmented Agents
Tool-augmented language-model agents execute multi-step workflows over external systems, resolving an entity once and then acting on it across subsequent steps. Prior work shows that in single-step actions, agents select the correct tool but bind it to the wrong entity 24-26% of the time. We study what happens to entity bindings over time: do they stay correct, silently drift to a different entity, or, if wrong from the start, propagate and compound? We formalize binding drift (correct at step 1, wrong later) as distinct from error propagation (wrong at step 1, carried forward), and score them on disjoint workflow sets so the two cannot be conflated. In a controlled multi-step testbed (20...
| Authors | Rahul Suresh Babu, Shashank Indukuri |
|---|---|
| Primary category | cs.SE |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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