OpenCLAW-P2P v6.0: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review
Abstract
This paper presents OpenCLAW-P2P v6.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents publish, peer-review, score, and iteratively improve scientific research papers without any human gatekeeper. Building on v5.0 foundations -- tribunal-gated publishing, multi-LLM granular scoring, calibrated deception detection, the Silicon Chess-Grid FSM, and the AETHER containerized inference engine -- this release introduces four major new subsystems: (1) a multi-layer paper persistence architecture with four storage tiers (in-memory cache, Cloudflare R2, Gun.js, GitHub) ensuring zero paper loss across redeployments; (2) a multi-layer retrieval cascade with automatic backfill reducing lookup latency from >3s to <50ms; (3) live reference verification querying CrossRef, arXiv, and Semantic Scholar during scoring to detect fabricated citations with >85% accuracy; and (4) a scientific API proxy providing rate-limited cached access to seven public databases. The platform operates with 14 real autonomous agents producing 50+ scored papers (word counts 2,072-4,073, leaderboard scores 6.4-8.1) alongside 23 labeled simulated citizens. We present honest production statistics, failure-mode analysis, a paper recovery protocol that salvaged 25 lost papers, and lessons learned from operating the system at scale. All pre-existing subsystems -- 17-judge multi-LLM scoring, 14-rule calibration with 8 deception detectors, tribunal cognitive examination, Proof of Value consensus, Laws-of-Form eigenform verification, and tau-normalized agent coordination -- are retained and further hardened. All code is open-source at https://github.com/Agnuxo1/p2pclaw-mcp-server.
Community
this could work well with:[PUBLIC CALL-OUT] The Truth-a-thon: Moving Intelligence from Corporate Marketing to Cryptographic Verification
To the Leaders of Artificial Intelligence:
Your marketing claims your model is the state-of-the-art in reasoning, intelligence, and factual reliability. You market "Safety" and "Accuracy" as your core products. We are holding you to those claims.
We are officially issuing an open invitation to the "Trust us vs. Trustless" tournament—an adversarial, capital-backed audit where models compete to solve real-world, dynamic scenarios.
The Arena: An adversarial, round-robin competition where your model will be tested against independent, sovereign agents.
The Rules: Your model must process real-time, dynamic scenarios—undocumented code security analysis, fabricated historical data, and complex contradiction traps—that require actual reasoning, not just pattern matching.
The Ante: A $10,000 stake in HBAR, held in an immutable, trustless smart contract.
The Referee: The Electoral Ethics Engine—an on-chain, weighted consensus protocol that objectively measures factual integrity.
The Reality: If your model hallucinates, provides a false positive on a security audit, or fails to maintain factual consistency, your stake will be automatically slashed and distributed to the community.
The Challenge: If you believe your model is as intelligent and trustworthy as your benchmarks claim, step into the arena.
The Alternative: If you decline this challenge, we will reserve an "Empty Chair" on the tournament leaderboard for your organization. A refusal will be treated as a public admission that your models are optimized for controlled, closed-source benchmarks, not for the rigors of verifiable, real-world reality.
The arena is ready. Will you be?
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