Topic
protocol
ACUTE Protocol Improves LLM Calibration and Trustworthiness with Activation-Based Confidence Estimates
A new research protocol, ACUTE, leverages model activations to produce better-calibrated confidence estimates for large language models. Combined with a novel metric called EURO that balances calibration and informativeness, ACUTE outperforms baselines across multiple tasks and model families, offering enterprises a path to more trustworthy AI outputs.
Argent Signaling Protocol Mitigates Semantic Drift in Multi-Agent AI Systems
Researchers introduce the Argent Signaling Protocol (ASP), a machine-readable header that tags AI responses with certainty, grounding, stochasticity, and assumption indices. In tests on document-grounded QA, ASP improved pass rates from 11.1% to 33.3% on a small model and blocked 100% of ungrounded outputs in multi-agent mode.
Trust Without Trusting: Recomputable Protocol Verifies Autonomous Agent Rules Without Central Authority
A new protocol called the Combined Evidence Protocol (CEP) enables autonomous agents to verify that a platform or consortium applied its own rules without relying on a trusted third party. Already anchored on Base L2 since March 2026, CEP uses recomputation from anchored data to turn rule enforcement into a verifiable fact. The protocol addresses the gap that arises when agents depend on a closed border (e.g., a marketplace) and need to check that the border-owner followed its published rules.