AI RESEARCH

Tool-Call Dependency Structure is Linearly Decodable in LLM Agent Residual Streams

arXiv CS.CL

ArXi:2605.25310v1 Announce Type: new Tool-using LLM agents produce trajectories whose calls form a directed dependency graph: earlier tool outputs supply arguments to later calls. Whether this execution structure is represented inside the model is unknown; prior structural probes have targeted static code or chain-of-thought text, not an agent's run-time call graph. A low-capacity edge probe on the residual stream of Qwen3-32B decodes the tool-call dependency graph well above both a Hewitt--Liang random-label control and a positional baseline.