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README.md

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 This repository contains code, data, and templates for crowdsourcing protocols, described by the paper: [Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries](https://arxiv.org/abs/2109.09195).
 
-## 
-
+## Scripts
 calculate.ipynb: to calculate the score distribution, krippendorff reliability, and SHR reliability.
 
+## Data
+
+We released our evaluation templates and annotations to promote future work on factual consistency evaluation. The annotations can be found in [for CNN&DM data](https://drive.google.com/file/d/17d8-CkgCariNGyfftMwW0klV8kFY7xRf/view?usp=sharing), [for XSUM data](https://drive.google.com/file/d/1PiWmNE4rmisBfYNjzv36viMnxN9RVKle/view?usp=sharing) and [templates](https://drive.google.com/file/d/1i_Qq_kPFRWhh1DTu2KxEwBV_fBtPHd1W/view?usp=sharing)
+
+## Model
+
+The code for BART, ProphetNet, PEGASUS, and BERTSUM is based on Fairseq(-py). Our pretrained models can be found in [for CNN&DM data](https://drive.google.com/file/d/1S4xNrtykxkNfoEo4V_RJX6fvbRkpr_KB/view?usp=sharing) and [for XSUM data]()
+
 ## Citation
 If you use our code in your research, please cite our work:
 ```bibtex