DGrid AI released the latest research paper PoQ-Judge, completing the closed loop of decentralized LLM quality assessment with a multi-architecture evaluation framework
The decentralized AI infrastructure network DGrid AI today released its latest research paper "PoQ-Judge," proposing a multi-architecture quality assessment framework that does not require reference answers. This means that in real deployment environments, there are often no standard answers for comparison, yet the protocol can still reliably score the quality of model responses and allocate incentives accordingly. This is a key piece that has long been missing in DGrid's decentralized LLM inference quality assessment system.
PoQ (Proof of Quality) is a consensus mechanism independently developed by DGrid, designed to prevent model providers from deploying low-quality models, fabricating data, or hiding computational costs at the protocol level, thereby ensuring service quality and pricing transparency. The DGrid team has been continuously working on PoQ and has published four research papers to date. The newly released PoQ-Judge has trained three assessment models covering different quality and cost scenarios, achieving a correlation of up to 0.747 with human scoring on the retention test set, significantly outperforming all previous reference answer-based evaluators, while reducing assessment costs by over 72% through cascading evaluation and online weight calibration.
With the implementation of PoQ-Judge, the entire process from quality assessment → scoring → incentive allocation has completely eliminated reliance on reference answers, thus establishing a closed loop for the quality of decentralized LLM inference.
DGrid AI is a decentralized AI intelligent network dedicated to building an open, transparent, and community-driven AI infrastructure. Focusing on model invocation and application experience, DGrid has launched several core products: the AI Gateway that aggregates mainstream large models globally, the one-click deployment platform for AI agents DClaw, the anonymous model competition platform AI Arena, and the intelligent model recommendation assistant Dori, providing one-stop services for developers and users. It is reported that DGrid AI's revenue has surpassed 20 million dollars in six months.
You may also like
What you bought on CEX is really not US stocks: Analyzing the 94% liquidation monopoly and the evaporation of equity under a five-layer pipeline
In such a crowded cross-border payment arena, where is the next stop for the future?
Why Is Bitcoin Down in 2026? What We Can Learn From 2022
The large models in the United States are moving towards closure in the name of security
From the white-haired stock god to the billionaire fund mogul, the smart people shorting Nvidia are all getting rich using the same framework
Morning Report | CoinEx becomes a key hub for Iran to evade sanctions, involving over $3.8 billion in funds; Kalshi seeks a new round of financing, with a valuation potentially rising to $40 billion
Global Launch: As predictions become the most scarce asset in the AI era, Manadia is defining the next generation of the value internet
Why do cryptocurrency projects always like to change their names?
Who is footing the bill for the $64 billion accounting frenzy?
I never expected that the first application of AI x Crypto would be in security auditing
What is your view on Binance's competitive advantages?
ETH has entered a non-consensus phase, and the turning point is approaching!
The shift in the cloud of the air: from despising stablecoins a year ago to the high-profile entry of capital today
The survival dilemma of small and medium exchanges behind the withdrawal anomalies exposed by AscendEX
Why Is Bitcoin Falling Below $60K? 5 Key Market Drivers Explained
Bitcoin has dropped sharply amid ETF outflows, Strategy stock weakness, AI stock rallies, and changing Fed expectations. Explore the key forces driving BTC’s latest correction and what traders should watch next.



