Beyond Aggregate Risk: Role-Stratified Conformal Risk Control for LLM Tool Calls
Language-model agents act through structured tool calls whose arguments carry very different risks: untrusted content may legitimately shape an email body but should never set a recipient, account, command, or credential. Existing conformal risk control methods certify a tool call as a whole, so a failure in one rare high-risk field can be averaged away by the many benign arguments around it, leaving the argument that causes harm uncertified. We introduce role-stratified per-field conformal risk control, a calibration layer that wraps any per-field detector and assigns a separate threshold and risk budget to each semantic argument role. We show that aggregate certification pays a price of...
| Authors | Md Ashikur Rahman, Md Arifur Rahman, Niamul Hassan Samin et al. |
|---|---|
| Primary category | cs.LG |
| Published | 27 July 2026 |
| Last updated at source | 31 July 2026 |
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