Fusion-in-Decoder (FiD) is a model described in the following paper:

> Izacard, Gautier, and Édouard Grave. [Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://aclanthology.org/2021.eacl-main.74/). _Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume_. 2021.

 We have replicated FiD training with our Wikipedia corpus variants and incorporated the model into our [PyGaggle](https://github.com/castorini/pygaggle) neural text ranking library.

Our own efforts are described in the paper entitled: 
> Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.

This is a FiD-large reader model for the wiki-text-6-3 corpus variant trained on the TriviaQA dataset.