ThoughtfulThings/sasha_smart_home_reasoning
收藏Hugging Face2025-03-02 更新2025-11-01 收录
下载链接：
https://hf-mirror.com/datasets/ThoughtfulThings/sasha_smart_home_reasoning
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资源简介：
---
dataset_info:
features:
- name: id
dtype: string
- name: home
dtype: string
- name: command
dtype: string
- name: goal_type
dtype: string
- name: goal_category
dtype: string
- name: prompt
dtype: string
- name: temperature
dtype: float64
- name: response
dtype: string
- name: time_elapsed
dtype: float64
- name: usage
dtype: string
- name: model
dtype: string
- name: devices
dtype: string
- name: sensors
dtype: string
- name: relevant_device_types
dtype: string
- name: home_supports_goal
dtype: bool
splits:
- name: train
num_bytes: 550546
num_examples: 120
download_size: 63591
dataset_size: 550546
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: mit
tags:
- llm
- smarthome
- reasoning
- finetune
---
This is a dataset of smart home user commands and JSON responses generated by zero-shot prompting of GPT-4. It can be used to fine-tune and/or evaluate language models for responding to user commands in smart homes. For more information, refer to our paper [Sasha: Creative Goal-Oriented Reasoning in Smart Homes with Large Language Models](https://dl.acm.org/doi/abs/10.1145/3643505).
https://arxiv.org/abs/2305.09802
If you use the dataset in your work, please cite us:
```
@article{king2024sasha,
title={Sasha: creative goal-oriented reasoning in smart homes with large language models},
author={King, Evan and Yu, Haoxiang and Lee, Sangsu and Julien, Christine},
journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
volume={8},
number={1},
pages={1--38},
year={2024},
publisher={ACM New York, NY, USA}
}
```
提供机构：
ThoughtfulThings
