Agentic Commerce World: An Auditable and Verifiable Environment for Vibe Commerce
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
In vibe coding, people describe software in natural language and delegate implementation to AI agents. By analogy, vibe commerce allows people to express buying or selling goals in natural language and delegate the corresponding tasks to agents. Commerce, however, requires independently controlled Buyer and Merchant agents to interact in a shared market while preserving their private objectives and distinct authority. We introduce Agentic Commerce World (ACWorld), an environment for evaluating such agents across ongoing transactions. Through its Vibe Commerce Protocol (VCP), ACWorld validates agent actions before updating shared transaction state and records the resulting interactions, making agent behavior auditable and evaluation reproducible. The ACWorld Benchmark contains a 200-task capability-coverage track and a 60-task large-catalog track that searches 785,022 transactable listings. Across ten models, mean scores range from 65.9% to 85.6% and from 56.1% to 91.4%, respectively. Our analysis shows that process-level evidence is necessary: final state alone can miss evaluated errors, incomplete trajectories still retain useful process signals, and large-catalog tasks expose bottlenecks across stages.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 31 of its 44 references that are in the map. First posted on arXiv 3 Aug 2026.
Builds on
31 of 44 references.
Closest ancestors · 9
Same direction, newest first
- 2026EComAgentBench: Benchmarking Shopping Agents on Long-Horizon Tasks with Distributed Hidden Intent16 Jun
- 2026CoffeeBench: Benchmarking Long-Horizon LLM Agents in Heterogeneous Multi-Agent Economies15 Jun
- 2026RetailBench: Benchmarking long horizon reasoning and coherent decision making of LLM agents in realistic retail environments14 Jun
- 2026ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents15 May
- 2026TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Rate13 May
- 2025WebMall -- A Multi-Shop Benchmark for Evaluating Web Agents18 Aug
- 2025ShoppingBench: A Real-World Intent-Grounded Shopping Benchmark for LLM-based Agents6 Aug
- 2025What Is Your AI Agent Buying? Evaluation, Biases, Model Dependence, & Emerging Implications for Agentic E-Commerce4 Aug
- 2023Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia6 Dec
Other references · 22
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
- 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
- 2023AgentBench: Evaluating LLMs as Agentscited by 1,211
- 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
- 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
- 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,134
- 2023GAIA: a benchmark for General AI Assistantscited by 1,084
- 2025τ2-Bench: Evaluating Conversational Agents in a Dual-Control Environmentcited by 558
- 2024AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agentscited by 359
- 2024ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilitiescited by 272
- 2020PettingZoo: Gym for Multi-Agent Reinforcement Learningcited by 209
- 2025MultiAgentBench: Evaluating the Collaboration and Competition of LLM agentscited by 169
10 more
- 2026CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verificationcited by 117
- 2026Kimi K3: Open Frontier Intelligencecited by 99
- 2021Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Potcited by 97
- 2025Magentic Marketplace: An Open-Source Environment for Studying Agentic Marketscited by 15
- 2026AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactionscited by 11
- 2026Beyond Math and Code: Lightweight Corpus-Grounded Process Rewards for Factual Question Answeringcited by 4
- 2026RAILS: Verification-Native Clearing For Agentic Commercecited by 2
- 2026Shopping Reasoning Bench: An Expert-Authored Benchmark for Multi-Turn Conversational Shopping Assistantscited by 2
- 2026Strategic Exploitation in LLM Agent Markets: A Simulation Framework for E-Commerce Trustcited by 1
- 2026A Decision-Centered Reference Architecture for Trustworthy Agentic Commercecited by 1
Built on by
Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2026MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations
- 2026Bittensor Agent Arenas as a Trajectory Primitive: Distilling a Shopping Agent from ShoppingBench Subnet Traces
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
- 2026Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commerce
- 2026E-Commerce Bench: Evaluating LLM Agents on Long-Horizon Autonomous Business Operation
- 2026TessPay: Verify-then-Pay Infrastructure for Trusted Agentic Commerce
- 2026Verifiable Hidden Dynamics Play: Generating Agentic RL Environments from Solved Mechanisms
- 2026AgenticShop: Benchmarking Agentic Product Curation for Personalized Web Shopping