X-Agent

This repository contains code and data to reproduce the results in the paper: Answering XAI questions in a conversational agent setting

Data

Original data with pairs of paraphrases for XAI and their annotated scores (described in section 3) can be found here

The filtered data, which is corresponding to "XAI question phrase bank" in the paper can be found here

Computational Environment

Install dependencies via conda:

conda env update -f environment.yml
conda activate xagent
pip install -e .

Start jupyter notebook:

jupyter notebook

NLU evaluation

• Reproducibility NLU (Section 5) example command: python run_nlu.py -M simcse-dnn -Q all
  • Replace "simcse-dnn" by "svm", "rf", "simcse" to get the results of other models.
  • Replace "all" by "xai" to get the results on xai question set

Demo

1. Open X-Agent demo in notebook
2. Run all cells in the notebook
3. Have fun

Note:

• The interface rendering by local jupyter notebook looks better than rendering by github.

Reference and Citation

Please refer to our work when using or discussing PIP-Net:

Van Bach Nguyen, Jörg Schlötterer, Christin Seifert (2023). “From Black Boxes to Conversations: Incorporating XAI in a Conversational Agent.". World Conference Explainable Artificial Intelligence (XAI).

BibTex citation:

@InProceedings{Nguyen2023_wcxai_xagent,
  author    = {Nguyen, Van Bach and Schl{\"o}tterer, J{\"o}rg and Seifert, Christin},
  booktitle = {Proc. World Conference Explainable Artificial Intelligence (XAI)},
  title     = {From Black Boxes to Conversations: Incorporating XAI in a Conversational Agent},
  year      = {2023},
}