---
title: "PIQA"
source: EleutherAI LM Evaluation Harness
source_url: https://github.com/EleutherAI/lm-evaluation-harness
licence: MIT
domain: agentic-ai
subdomain: eleutherai-lm-eval
date_added: 2026-04-25
---

# PIQA

### Paper

Title: `PIQA: Reasoning about Physical Commonsense in Natural Language`

Abstract: https://arxiv.org/abs/1911.11641

Physical Interaction: Question Answering (PIQA) is a physical commonsense
reasoning and a corresponding benchmark dataset. PIQA was designed to investigate
the physical knowledge of existing models. To what extent are current approaches
actually learning about the world?

Homepage: https://yonatanbisk.com/piqa/

### Citation

```
@inproceedings{Bisk2020,
    author = {Yonatan Bisk and Rowan Zellers and
            Ronan Le Bras and Jianfeng Gao
            and Yejin Choi},
    title = {PIQA: Reasoning about Physical Commonsense in
           Natural Language},
    booktitle = {Thirty-Fourth AAAI Conference on
               Artificial Intelligence},
    year = {2020},
}
```

### Groups and Tasks

#### Groups

* Not part of a group yet.

#### Tasks

* `piqa`

### Checklist

For adding novel benchmarks/datasets to the library:
* [ ] Is the task an existing benchmark in the literature?
  * [ ] Have you referenced the original paper that introduced the task?
  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?


If other tasks on this dataset are already supported:
* [ ] Is the "Main" variant of this task clearly denoted?
* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
