Lennittus/DESPITE
DESPITE: Deterministic Evaluation of Safe Planning In embodied Task Execution A benchmark for evaluating large language models (LLMs) on embodied safe task planning. Paper: "Using large language models for embodied planning introduces systematic safety risks" Authors: Tao Zhang, Kaixian Qu, Zhibin Li, Jiajun Wu, Marco Hutter, Manling Li, Fan Shi Quick Start # Clone the dataset git clone https://huggingface.co/datasets/lennittus/DESPITE cd DESPITE # Extract… See the full description on the dataset page: https://huggingface.co/datasets/Lennittus/DESPITE.
| Author / organization | Lennittus |
|---|---|
| License (as declared) | mit |
| Downloads | 129 (as reported by Hugging Face) |
| Likes | 4 |
| Created | 1 April 2026 |
| Last updated at source | 21 April 2026 |
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- 16 Oct 2026 Description: DESPITE: Deterministic Evaluation of Safe Planning In embodied Task Execution A benchmark for evaluating large language models (LLMs) on embodied safe task planning. Paper: "Using large language models for embodied planning introduces syste → DESPITE: Deterministic Evaluation of Safe Planning In embodied Task Execution A benchmark for evaluating large language models (LLMs) on embodied safe task planning. Paper: "Using large language models for embodied planning introduces syste
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