Psych-101

### Dataset Summary

Psych-101 is a data set of natural language transcripts from human psychological experiments.
It comprises trial-by-trial data from 160 psychological experiments and 60,092 participants, making 10,681,650 choices.
Human choices are encapsuled in "<<" and ">>" tokens.

- **Paper:** [Centaur: a foundation model of human cognition](https://marcelbinz.github.io/imgs/Centaur__preprint_.pdf)
- **Point of Contact:** [Marcel Binz](mailto:[e-mail])

### Example Prompt

```
You will be presented with triplets of objects, which will be assigned to the keys D, P, and H.
In each trial, please indicate which object you think is the odd one out by pressing the corresponding key.
In other words, please choose the object that is the least similar to the other two.

D: piecrust, P: game, and H: bracelet. You press <<D>>.
D: tuning fork, P: rocket, and H: waffle iron. You press <<P>>.
D: grits, P: combination lock, and H: suitcase. You press <<D>>.
D: boulder, P: odometer, and H: salami. You press <<P>>.
D: spoon, P: diaper, and H: satellite dish. You press <<P>>.
[...]
```

### Languages

English.

### Usage

```
from datasets import load_dataset
data = load_dataset('marcelbinz/Psych-101')
```

### Data Fields

```
{
"text": Natural language transcription of the experiment.
"experiment": Identifier for the experiment.
"participant": Identifier for the participant.
}
```

### Licensing Information

[Apache License 2.0](https://choosealicense.com/licenses/apache-2.0/)

### Citation Information

```
@misc{binz2024centaurfoundationmodelhuman,
title={Centaur: a foundation model of human cognition},
author={Marcel Binz and Elif Akata and Matthias Bethge and Franziska Brändle and Fred Callaway and Julian Coda-Forno and Peter Dayan and Can Demircan and Maria K. Eckstein and Noémi Éltető and Thomas L. Griffiths and Susanne Haridi and Akshay K. Jagadish and Li Ji-An and Alexander Kipnis and Sreejan Kumar and Tobias Ludwig and Marvin Mathony and Marcelo Mattar and Alireza Modirshanechi and Surabhi S. Nath and Joshua C. Peterson and Milena Rmus and Evan M. Russek and Tankred Saanum and Natalia Scharfenberg and Johannes A. Schubert and Luca M. Schulze Buschoff and Nishad Singhi and Xin Sui and Mirko Thalmann and Fabian Theis and Vuong Truong and Vishaal Udandarao and Konstantinos Voudouris and Robert Wilson and Kristin Witte and Shuchen Wu and Dirk Wulff and Huadong Xiong and Eric Schulz},
year={2024},
eprint={2410.20268},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2410.20268},
}
```

### 数据集概述
Psych-101是一个源自人类心理学实验的自然语言转录数据集。该数据集包含160项心理学实验与60092名被试的逐试次数据，总计生成10681650次选择行为。人类的选择结果被封装在`<<`与`>>`标记（Token）中。
- **相关论文：** [Centaur：人类认知基础模型（Centaur: a foundation model of human cognition）](https://marcelbinz.github.io/imgs/Centaur__preprint_.pdf)
- **联系人：** [Marcel Binz](mailto:[e-mail])

### 示例提示

您将收到三组对象，它们将被分配至键D、P与H。
在每一试次中，请通过按下对应按键，指出您认为的异类对象。
换言之，请选择与另外两者相似度最低的对象。

D: 酥皮饼，P: 游戏，H: 手镯。您按下<<D>>。
D: 音叉，P: 火箭，H: 华夫饼烤模。您按下<<P>>。
D: 粗燕麦粉，P: 密码锁，H: 手提箱。您按下<<D>>。
D: 巨砾，P: 里程表，H: 萨拉米香肠。您按下<<P>>。
D: 勺子，P: 尿布，H: 卫星天线。您按下<<P>>。
[...]

### 语言
英语。

### 使用方式

from datasets import load_dataset
data = load_dataset('marcelbinz/Psych-101')

### 数据字段

{
"text": 实验的自然语言转录内容。
"experiment": 实验标识符。
"participant": 被试标识符。
}

### 授权协议
[Apache许可证2.0](https://choosealicense.com/licenses/apache-2.0/)

### 引用信息

@misc{binz2024centaurfoundationmodelhuman,
title={Centaur: a foundation model of human cognition},
author={Marcel Binz 和 Elif Akata 和 Matthias Bethge 和 Franziska Brändle 和 Fred Callaway 和 Julian Coda-Forno 和 Peter Dayan 和 Can Demircan 和 Maria K. Eckstein 和 Noémi Éltető 和 Thomas L. Griffiths 和 Susanne Haridi 和 Akshay K. Jagadish 和 Li Ji-An 和 Alexander Kipnis 和 Sreejan Kumar 和 Tobias Ludwig 和 Marvin Mathony 和 Marcelo Mattar 和 Alireza Modirshanechi 和 Surabhi S. Nath 和 Joshua C. Peterson 和 Milena Rmus 和 Evan M. Russek 和 Tankred Saanum 和 Natalia Scharfenberg 和 Johannes A. Schubert 和 Luca M. Schulze Buschoff 和 Nishad Singhi 和 Xin Sui 和 Mirko Thalmann 和 Fabian Theis 和 Vuong Truong 和 Vishaal Udandarao 和 Konstantinos Voudouris 和 Robert Wilson 和 Kristin Witte 和 Shuchen Wu 和 Dirk Wulff 和 Huadong Xiong 和 Eric Schulz},
year={2024},
eprint={2410.20268},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2410.20268},
}

搜集汇总

背景与挑战

背景概述

Psych-101是一个心理学实验自然语言转录数据集，包含来自160个实验、60,092名参与者的试次数据，总计10,681,650个选择，人类选择以'<<'和'>>'标记封装。数据集用于研究人类认知行为，提供实验文本、实验标识和参与者标识字段，适用于心理学和人工智能模型训练。