Abhay Bhandarkar
Author directory2026
Vouch: Counterfactual Contracts for Multi-Agent Coordination
Abhay Bhandarkar | Vedanth Nanesha
Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026
Abhay Bhandarkar | Vedanth Nanesha
Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026
Multi-agent LLM coordination typically reduces to voting or arbitration over self-reported labels and reasoning that is uncoupled from agent behavior and fails predictably under structured bias. A shortcut-reliant agent is confident about its shortcut, and its predictions survive any rule that consults only self-reports. We propose VOUCH, a coordination protocol in which every agent claim is coupled to a deterministic test the protocol runs itself. An agent commits to a counterfactual prediction about an intervention’s outcome; the protocol applies the intervention and verifies the contract only if the actual outcome matches. The natural single-side instantiation is unsound as a self-coherent agent satisfies its own commitment by construction. We resolve this with a dual-side construction where the proposer additionally commits to a second agent’s post-intervention prediction, a cross-side claim that self-coherence cannot fulfill. Across multimodal classification (Hateful Memes, CrisisMMD, MM-IMDb), code (MBPP, HumanEval), and math (GSM8K, MATH, SVAMP), the dual-side fix reduces wrong-verified events by 46%–85% per domain while never falling more than 1 point below the Ensemble baseline on accuracy. VOUCH is therefore designed not to outperform ensembling, but to preserve task accuracy while making coordination decisions testable and auditable.