| --- |
| license: apache-2.0 |
| task_categories: |
| - fill-mask |
| - text-classification |
| language: |
| - en |
| pretty_name: EXPRESS |
| tags: |
| - emotion |
| - psychology |
| --- |
| |
| # EXPRESS Dataset |
|
|
| ## Overview |
| This is the EXPRESS dataset from the paper: |
| https://arxiv.org/pdf/2509.09593 |
|
|
| EXPRESS (EXperiences and PRocessed Emotions in Self-disclosure Stories) is a benchmark dataset for evaluating fine-grained emotion recognition in language models. It contains 33,679 naturally occurring Reddit-based human experiences paired with self-disclosed emotion labels. |
|
|
| EXPRESS uses emotions explicitly disclosed by the original authors as ground-truth labels. The dataset covers 251 fine-grained emotion labels and an average context length of 259 words, enabling evaluation of models’ ability to infer nuanced emotional states from rich real-world contexts. |
|
|
| Each instance masks the self-disclosed emotion word or phrase in the original text using a `<mask>` token. |
|
|
| ## Usage |
|
|
| You can load the dataset with: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("bangzhao/express-emotion-recognition") |
