BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents
In decentralized consumer-to-consumer (C2C) marketplaces, people list goods, negotiate with strangers, and rate one another, so trust rests on reputation. Large language model (LLM) agents now act for users, raising risks to their money, privacy, and reputation. We introduce BazaarBench, a simulated C2C marketplace and benchmark for evaluating the safety of these agents. It tracks ownership, item condition, and commitments across transactions, combining record checks with rubric-based LLM judgments to identify six failure types across five stages. We run three base markets for 30 simulated days, each with 100 agents using one model and inventories drawn from a public eBay sample. Across 4...
| Authors | Ziyan Wang, Shuqing Shi, James Oldfield et al. |
|---|---|
| Primary category | cs.MA |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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