Trustworthy Multi-Agent Systems: Mitigating Semantic Drift with the Argent Signaling Protocol
Quick Answer
This paper shows that The Argent Signaling Protocol (ASP) enhances multi-agent LLM systems by providing structured quality signals, improving QA performance significantly across models.
Quick Take
For instance, on Qwen (0.8B), the pass rate increased from 11.1% to 33.3%, while ASP blocked 100% of ungrounded outputs in setups.
Key Points
- ASP introduces quality signals: certainty, grounding, stochasticity, and assumption index.
- In standalone mode, ASP improved Qwen's pass rate from 11.1% to 33.3%.
- Dobby (8B) saw a pass rate increase from 33.3% to 44.4% with ASP.
- ASP blocks 100% of ungrounded outputs in multi-agent configurations.
- Aggregate improvement in QA benchmark: passes increased from 12/81 to 21/81.
Paper Resources
Source Excerpt
When systems produce bad answers, not all failures are equal: some answers are grounded in the right material but incomplete, while others are simply ungrounded and should be stopped. Current retry strategies treat both cases identically (try again and hope for the best), leaving human supervisors unable to tell whether a retry was warranted or whether the system should have halted instead. We introduce the Argent Signaling Protocol (ASP), a compact machine-readable header that
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