Code for paper accepted at EMNLP 2025 Findings: Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems (Wang et al., 2025)
3
stars
220
commits
Python
primary language
Aug 23, 2025
updated
Note: Our paper gets accepted at EMNLP 2025 Findings!
conda create -n <name> python=3.10.0
conda activate <name>
pip install -r requirements.txt
βββ Compass
β βββ experiment
β β βββ custom_input_extraction
β β βββ intent recognition
β βββ data
β βββ cn
β βββ de
β βββ en
β βββ ru
β βββ te
β βββ testset
βββ MultiCoXQL
βββ experiment
β βββ data
β βββ parsing
β β βββ guided_decoding
β β βββ multi_prompt
β β βββ multi_prompt_plus
β βββ results
βββ data

@misc{wang2025multilingualdatasetscustominput,
title={Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems},
author={Qianli Wang and Tatiana Anikina and Nils Feldhus and Simon Ostermann and Fedor Splitt and Jiaao Li and Yoana Tsoneva and Sebastian MΓΆller and Vera Schmitt},
year={2025},
eprint={2508.14982},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2508.14982},
}
Python
89.2%
Jupyter Notebook
10.8%
Code for paper accepted at EMNLP 2025 Findings: Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems (Wang et al., 2025)
3
stars
220
commits
Python
primary language
Aug 23, 2025
updated
Note: Our paper gets accepted at EMNLP 2025 Findings!
conda create -n <name> python=3.10.0
conda activate <name>
pip install -r requirements.txt
βββ Compass
β βββ experiment
β β βββ custom_input_extraction
β β βββ intent recognition
β βββ data
β βββ cn
β βββ de
β βββ en
β βββ ru
β βββ te
β βββ testset
βββ MultiCoXQL
βββ experiment
β βββ data
β βββ parsing
β β βββ guided_decoding
β β βββ multi_prompt
β β βββ multi_prompt_plus
β βββ results
βββ data

@misc{wang2025multilingualdatasetscustominput,
title={Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems},
author={Qianli Wang and Tatiana Anikina and Nils Feldhus and Simon Ostermann and Fedor Splitt and Jiaao Li and Yoana Tsoneva and Sebastian MΓΆller and Vera Schmitt},
year={2025},
eprint={2508.14982},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2508.14982},
}
Python
89.2%
Jupyter Notebook
10.8%