NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning
While explicit goals may render certain actions optimal, implicit social norms often impose hidden constraints. Existing evaluations typically focus on explicit goal achievement or direct norm knowledge, seldom assessing whether planners can infer and apply these hidden constraints within action sequences. We introduce NormAct, a benchmark for embodied social-norm interactions that evaluates plans on Goal Achievement, Norm Compliance, and overall Task Success.
- ▪While explicit goals may render certain actions optimal, implicit social norms often impose hidden constraints.
- ▪Existing evaluations typically focus on explicit goal achievement or direct norm knowledge, seldom assessing whether planners can infer and apply these hidden constraints within action sequences.
- ▪We introduce NormAct, a benchmark for embodied social-norm interactions that evaluates plans on Goal Achievement, Norm Compliance, and overall Task Success.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2606.27826 |
| Publication time | Mon, 29 Jun 2026 00:00:00 -0400 |
| Retrieval time | 2026-06-29T07:20:58.035Z |
| Last seen | 2026-06-29T07:20:58.035Z |
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Computer Science > Artificial Intelligence arXiv:2606.27826 (cs) [Submitted on 26 Jun 2026] Title:NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning Authors:Shiyun Zhao, Xinwei Song, Tianyu Guo, Xiaomeng Gao, Mingyuan Liu, Xu Han, Yuanyuan Zhang, Zhenliang Zhang, Xue Feng, Bo Dai View a PDF of the paper titled NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning, by Shiyun Zhao and 9 other authors View PDF HTML (experimental) Abstract:Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only achieving instructed goals but also acting in socially appropriate ways.
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