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Bylines, paper authorship, correspondence addresses and the founder blurb under each post named an individual. They name the organisation that published the work instead: the brand on posts and pages, the research byline on papers, and research@ in place of a personal address. Both are what these repositories already used elsewhere — nothing new was coined. Co-authors are untouched. Where a paper named someone else alongside, they stay named; only the one byline changed. Bibliography entries, running heads, PDF metadata and affiliations move with it, so a citation still resolves to whoever the cited paper names. Sample and fixture data uses the placeholder name these tests already use elsewhere, so no assertion changed meaning. Co-authored-by: Hanzo Dev <[email protected]>
120 lines
4.5 KiB
TeX
120 lines
4.5 KiB
TeX
\documentclass[11pt,letterpaper]{article}
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\usepackage{shared/zoocover}
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% Packages
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\usepackage[utf8]{inputenc}
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\usepackage[T1]{fontenc}
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\usepackage{amsmath,amssymb,amsthm}
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\usepackage{algorithm}
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\usepackage{algorithmic}
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\usepackage{graphicx}
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\usepackage{hyperref}
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\usepackage{xcolor}
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\usepackage{booktabs}
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\usepackage{tikz}
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\usepackage{pgfplots}
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\pgfplotsset{compat=1.18}
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\usetikzlibrary{shapes,arrows,positioning,calc,decorations.pathreplacing}
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\usepackage{listings}
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\usepackage{caption}
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\usepackage{subcaption}
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\usepackage{enumitem}
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% geometry loaded by zoocover
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% Theorem environments
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\newtheorem{theorem}{Theorem}[section]
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\newtheorem{lemma}[theorem]{Lemma}
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\newtheorem{proposition}[theorem]{Proposition}
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\newtheorem{corollary}[theorem]{Corollary}
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\newtheorem{definition}{Definition}[section]
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\newtheorem{example}{Example}[section]
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% Custom commands
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\newcommand{\Zoo}{\textsc{Zoo}}
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\newcommand{\Lux}{\textsc{Lux}}
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\newcommand{\Beluga}{\textsc{Beluga}}
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\newcommand{\BLG}{\textsc{blg}}
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\newcommand{\PoAI}{\textsc{PoAI}}
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\newcommand{\DAO}{\textsc{dao}}
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\newcommand{\LLM}{\textsc{llm}}
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\newcommand{\TEE}{\textsc{tee}}
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\newcommand{\LoRA}{\textsc{LoRA}}
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\newcommand{\QLoRA}{\textsc{QLoRA}}
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\newcommand{\GRPO}{\textsc{grpo}}
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\newcommand{\DSO}{\textsc{dso}}
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% Solidity language definition (listings does not include it by default)
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\lstdefinelanguage{Solidity}{
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morekeywords={contract,function,returns,return,if,else,for,while,do,
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mapping,address,uint256,uint,int,bool,string,bytes,bytes32,
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public,private,internal,external,view,pure,payable,memory,storage,
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calldata,event,emit,modifier,require,struct,enum,interface,
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abstract,override,virtual,is,new,delete,import,pragma,solidity,
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library,using,constructor,msg,sender,block,timestamp,this,super},
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sensitive=true,
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comment=[l]{//},
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morecomment=[s]{/*}{*/},
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morestring=[b]",
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}
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% Listings style
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\lstset{
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basicstyle=\ttfamily\small,
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breaklines=true,
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frame=single,
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numbers=left,
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numberstyle=\tiny\color{gray},
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tabsize=2,
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captionpos=b,
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aboveskip=10pt,
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belowskip=10pt
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}
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% Hyperref setup
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\hypersetup{
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colorlinks=true,
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linkcolor=blue,
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citecolor=blue,
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urlcolor=blue
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}
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% Title and authors
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\title{\textbf{BELUGA}\\
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\large L3 App-Chain for AI Model Economics}
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\author{
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Zoo Labs Foundation Research\thanks{[email protected]}\\
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\textit{Zoo Labs Foundation}\\
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\texttt{[email protected]}
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}
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\date{January 2026}
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\begin{document}
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\zoocoverpage
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\begin{abstract}
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We present \Beluga{}, a Layer 3 application-specific blockchain for AI model economics, built on \Zoo{} Network (L2) which itself runs on \Lux{} Network (L0). \Beluga{} introduces a dedicated execution environment where every operation---model registration, inference requests, training bounties, data contribution---is a native transaction priced in the \BLG{} gas token. The chain implements custom EVM precompiles for inference pricing (address \texttt{0x0300}), a model marketplace, and training bounty escrow, enabling sub-millisecond settlement of AI compute transactions without leaving the chain. With a fixed supply of 100M \BLG{} allocated across a \DAO{} treasury (60M), inference pool (20M), training bounties (10M), and DEX liquidity (10M), \Beluga{} creates a self-sustaining economy where participants earn by training models, curating datasets, hosting inference, evaluating outputs, and governing the network. The chain runs on existing \Zoo{} validators via the \texttt{zood} node binary, requiring no new infrastructure. We describe the architecture, token economics, earning mechanisms, smart contract design, precompile specification, Proof of AI consensus adaptation, security model, and a concrete migration path from smart contracts on \Zoo{} to a sovereign L3. Experimental results from testnet deployment demonstrate 2,400 inference transactions per second with 1.1-second finality.
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\textbf{Keywords}: Layer 3 blockchain, AI model economics, inference marketplace, training bounties, application-specific chain
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\end{abstract}
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\tableofcontents
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\newpage
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%% ============================================================
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\input{sections/01-introduction}
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\input{sections/02-architecture}
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\input{sections/03-blg-token-economics}
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\input{sections/04-earning-mechanisms}
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\input{sections/05-smart-contracts}
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\input{sections/06-precompiles}
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\input{sections/07-consensus-poai-on-beluga}
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\input{sections/08-security-model}
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\input{sections/09-migration-path}
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\input{sections/10-related-work}
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\input{sections/99-conclusion}
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\end{document}
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