Human-LLM Deliberation as Interactive Proof: Conditions for Verifiability Without Transparency
When an LLM supplies an argument a user could not produce, how can the user decide whether to accept its claim? Inspired by interactive proofs, we pair a computationally unbounded LLM prover with a resource-bounded human verifier. The verifier checks requested details without seeing the LLM's internals; passed checks accumulate evidence toward an acceptance threshold. Given task-supplied bounds on false passes and human checking errors, we prove anytime-valid soundness against adaptive provers: the probability of ever accepting a false claim is at most a chosen error level. For a true claim, acceptance within the budget has probability at least the product of per-round probabilities that ...
| Authors | Baotong Zhang, Dean Foster, João Sedoc |
|---|---|
| Primary category | cs.CL |
| Published | 21 September 2026 |
| Last updated at source | 11 October 2026 |
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