CAVEAT: Towards Robust Computer-Use Agents in Incentive-Misaligned Environments
Computer-use agents (CUAs) increasingly act on behalf of users online. What happens when the environments they operate in have incentives of their own? Online marketplaces, for example, may favor some products over others, steering agents away from the user's objective. Existing CUA benchmarks cover cooperative settings or explicit attacks, but do not test whether agents preserve user objectives when the environment itself has a stake in the outcome. We introduce CAVEAT, a controlled benchmark spanning nine marketplace environments and a taxonomy of eight common steering mechanisms. Across five model families, agents purchase the user-optimal product in 78.6% of matched-control episodes b...
| Authors | Yuxuan Li, Will Epperson, Wesley Deng et al. |
|---|---|
| Primary category | cs.AI |
| Published | 23 September 2026 |
| Last updated at source | 27 September 2026 |
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