Toward faithful answer attribution with model internals 🌴

Authors (* Equal contribution): Jirui Qi* • Gabriele Sarti* • Raquel Fernández • Arianna Bisazza

Tip

This is the repository for reproducing all experimental results in our MIRAGE paper, accepted by the EMNLP 2024 Main Conference. Also, check our demo here!

If you find the paper helpful and use the content, we kindly suggest you cite through:

@inproceedings{Qi2024ModelIA,
  title={Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation},
  author={Jirui Qi and Gabriele Sarti and Raquel Fern'andez and Arianna Bisazza},
  year={2024},
  url={https://api.semanticscholar.org/CorpusID:270619780}
}

Environment:

For a quick start, you may load our environment easily with Conda:

conda env create -f MIRAGE.yaml

Alternatively, you can install all packages by yourself:

Python: 3.9.19

Packages: pip install -r requirements.txt

Reproduction of the alignment with human annotations (Experiments in Section 4)

The code is in the folder sec4_alignment. See more detailed instructions in the README.MD there.

Reproduction of citation generation and comparison with self-citation on long-form QA dataset ELI5 (Experiments in Section 5)

The code is in the folder sec5_longQA. See more detailed instructions in the README.MD there.