Datasets:
File size: 2,805 Bytes
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language:
- en
license: cc-by-sa-4.0
task_categories:
- text-generation
tags:
- recommendation-system
- user-simulation
dataset_info:
features:
- name: text
struct:
- name: action_list
sequence: string
- name: history
dtype: string
- name: profile
dtype: string
- name: user_id
dtype: string
- name: item_id
dtype: string
- name: timestamp
dtype: timestamp[ns]
- name: item_pos
dtype: int64
- name: choice_cnt
dtype: int64
- name: dataset
dtype: string
- name: impression_list
sequence: string
splits:
- name: test
num_bytes: 14699116
num_examples: 6400
download_size: 5555631
dataset_size: 14699116
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# UserMirrorer-eval
This is the evaluation set of **UserMirrorer**, presented in the paper [Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation](https://huggingface.co/papers/2508.18142).
**Code**: [Joinn99/UserMirrorer](https://github.com/Joinn99/UserMirrorer)
## Notice
In the `UserMirrorer` dataset, the raw data from `MIND` and `MovieLens-1M` datasets are distributed under restrictive licenses and cannot be included directly.
Therefore, we provide a comprehensive, step-by-step pipeline to load the original archives, execute all necessary preprocessing operations, and assemble the final UserMirrorer training and test splits.
Click [here](https://colab.research.google.com/github/UserMirrorer/UserMirrorer/blob/main/UserMirrorer_GetFullDataset.ipynb) to run the script notebook on Google Colab to get the full dataset. Also, you can download it and run it locally.
## Evaluation Usage
To run the evaluation, you can execute the following command provided in the official repository:
```bash
python usermirrorer/run_eval.py \
--project_path <YOUR_WORKING_DIR> \ # The path to your working directory
--model_path <MODEL_PATH> \ # The path to the model
--input_file <INPUT_FILE> \ # The path to the input file
--output_file <OUTPUT_FILE> \ # The path to the output file
--mode <MODE> \ # The mode of the evaluation
--repeat_times <REPEAT_TIMES> \ # The number of sampling times
```
## Citation
```bibtex
@misc{wei2025mirroringusersbuildingpreferencealigned,
title={Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation},
author={Tianjun Wei and Huizhong Guo and Yingpeng Du and Zhu Sun and Huang Chen and Dongxia Wang and Jie Zhang},
year={2025},
eprint={2508.18142},
archivePrefix={arXiv},
primaryClass={cs.HC},
url={https://arxiv.org/abs/2508.18142},
}
``` |