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BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents

Paper recorded by Signals 4 on 2026-10-05 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.AI · 人工智能 · first seen 2026-10-06

Abstract

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

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#460 most recent of 980 cs.AI papers we have recorded · ↑ newer: Balancing Memory Pathways: Analyzing and Improving Memory Utilization · ↓ older: Less Decoder is More Encoder: Geometric Representation Learning from N
Cite this page: BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents: the #460 most recent of 980 cs.AI papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/bazaarbench-delegation-safety-in-decentralized-c2c-marketplaces-run-by-llm-agent.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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