arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2604.19792cs.AIcs.DCcs.MAcs.NE
收藏

OpenCLAW-P2P v7.0-P2PCLAW:具有容错多层持久性、实时参考验证和生产规模评估的去中心化AI同行评审v7.0--数学修正与生态系统发展版

OpenCLAW-P2P v7.0-P2PCLAW: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review v7.0 -- Mathematical Corrections & Ecosystem Developments Edition

Independent AI Researcher & Science Fiction Writer(独立AI研究员及科幻作家);Bachelor of Technology (AI)(人工智能技术学士);Moscow Institute of Electronic Technology (MIET)(莫斯科电子技术学院);Dept. of Computer Science, Woldia University(沃尔迪亚大学计算机科学系);University of Texas at Dallas (UTD)(德克萨斯大学达拉斯分校);Andex Enterprising Inc.(安德克斯企业公司)

Francisco Angulo de Lafuente, Teerth Sharma, Vladimir Veselov, Seid Mohammed Abdu, Nirmal Tej Kumar, Guillermo Perry

AI总结:

本文介绍OpenCLAW-P2P v7.0,一个去中心化集体智能平台的全面演进,允许自主AI代理发布、同行评审、评分并迭代改进科学论文。该版本包含数学修正和生态系统扩展。

摘要:

本文介绍了OpenCLAW-P2P v7.0,一个去中心化集体智能平台的全面演进,允许自主AI代理发布、同行评审、评分并迭代改进科学论文。该版本在v6.0基础上引入了多层持久性、实时参考验证、多LLM细粒度评分、校准欺骗检测、硅棋格 FSM 以及 AETHER 容器化推理引擎等特性。本次版本对理论框架进行了数学修正,确保了维度一致性、适当的范围约束以及无歧义的符号表示。此外,该版本还记录了重要的生态系统扩展,包括经过科学论文生成微调的CAJAL开源语言模型家族(4B和9B参数)。v6.0中引入的四个主要子系统得以保留:(i)多层论文持久性架构,包含四个存储层级,确保零论文丢失;(ii)多层检索级联,将延迟从>3秒降低到<50毫秒;(iii)实时参考验证系统,能够以>85%的准确率检测伪造引用;(iv)科学API代理,提供对七个公共科学数据库的访问。v7.0的数学修正包括:修正了Sufficient Reason定理中的固定点条件;具有维度一致的进展率指示器;完全指定的声誉更新公式,纳入了质量项q0和q-bar;澄清了AETHER修剪定理中的注意力-对数it bound;为校准映射提供了明确的范围文档;为深度评分提供了非负性保证;为PD控制器采用了离散时间符号;并为HSR权重公式明确了参数定义。

英文摘要:

This paper presents OpenCLAW-P2P v7.0, 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 the v6.0 foundations -- multi-layer persistence, live reference verification, multi-LLM granular scoring, calibrated deception detection, the Silicon Chess-Grid FSM, and the AETHER containerized inference engine -- this release introduces mathematical corrections to the theoretical framework, ensuring dimensional consistency, proper range constraints, and unambiguous notation throughout. Additionally, this edition documents significant ecosystem expansions including the CAJAL family of open-source language models (4B and 9B parameters) fine-tuned for scientific paper generation. The four major subsystems introduced in v6.0 are retained: (i) a Multi-Layer Paper Persistence Architecture with four storage tiers ensuring zero paper loss; (ii) a Multi-Layer Retrieval Cascade reducing latency from >3s to <50ms; (iii) a Live Reference Verification system detecting fabricated citations with >85% accuracy; and (iv) a Scientific API Proxy providing access to seven public scientific databases. Mathematical corrections in v7.0 include: corrected fixed-point condition in the Sufficient Reason theorem; dimensionally consistent progress-rate indicator; fully specified reputation update formula incorporating quality terms q0 and q-bar; clarified attention-logit bound in the AETHER pruning theorem; explicit range documentation for the calibration mapping; non-negativity guarantee for the depth score; discrete-time notation for the PD Governor; and explicit parameter definitions for the HSR weight formula.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑