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Main Authors: Pan, Zhuoran, Li, Yue, Guan, Zhi, Hu, Jianbin, Chen, Zhong
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.04168
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author Pan, Zhuoran
Li, Yue
Guan, Zhi
Hu, Jianbin
Chen, Zhong
author_facet Pan, Zhuoran
Li, Yue
Guan, Zhi
Hu, Jianbin
Chen, Zhong
contents The increasingly complex Web3 ecosystem and decentralized finance (DeFi) landscape demand ever higher levels of technical expertise and financial literacy from participants. The Intent-Centric paradigm in DeFi has thus emerged in response, which allows users to focus on their trading intents rather than the underlying execution details. However, existing approaches, including Typed-intent design and LLM-driven solver, trade off expressiveness, trust, privacy, and composability. We present OMNIINTENT, a language-runtime co-design that reconciles these requirements. OMNIINTENT introduces ICL, a domain-specific Intent-Centric Language for precise yet flexible specification of triggers, actions, and runtime constraints; a Trusted Execution Environment (TEE)-based compiler that compiles intents into signed, state-bound transactions inside an enclave; and an execution optimizer that constructs transaction dependency graphs for safe parallel batch submission and a mempool-aware feasibility checker that predicts execution outcomes. Our full-stack prototype processes diverse DeFi scenarios, achieving 89.6% intent coverage, up to 7.3x throughput speedup via parallel execution, and feasibility-prediction accuracy up to 99.2% with low latency.
format Preprint
id arxiv_https___arxiv_org_abs_2603_04168
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle OMNIINTENT: A Trusted Intent-Centric Framework for User-Friendly Web3
Pan, Zhuoran
Li, Yue
Guan, Zhi
Hu, Jianbin
Chen, Zhong
Cryptography and Security
The increasingly complex Web3 ecosystem and decentralized finance (DeFi) landscape demand ever higher levels of technical expertise and financial literacy from participants. The Intent-Centric paradigm in DeFi has thus emerged in response, which allows users to focus on their trading intents rather than the underlying execution details. However, existing approaches, including Typed-intent design and LLM-driven solver, trade off expressiveness, trust, privacy, and composability. We present OMNIINTENT, a language-runtime co-design that reconciles these requirements. OMNIINTENT introduces ICL, a domain-specific Intent-Centric Language for precise yet flexible specification of triggers, actions, and runtime constraints; a Trusted Execution Environment (TEE)-based compiler that compiles intents into signed, state-bound transactions inside an enclave; and an execution optimizer that constructs transaction dependency graphs for safe parallel batch submission and a mempool-aware feasibility checker that predicts execution outcomes. Our full-stack prototype processes diverse DeFi scenarios, achieving 89.6% intent coverage, up to 7.3x throughput speedup via parallel execution, and feasibility-prediction accuracy up to 99.2% with low latency.
title OMNIINTENT: A Trusted Intent-Centric Framework for User-Friendly Web3
topic Cryptography and Security
url https://arxiv.org/abs/2603.04168