PyTorch implementation for ACL 2021 paper "Maria: A Visual Experience Powered Conversational Agent".

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Overview

Maria: A Visual Experience Powered Conversational Agent

This repository is the Pytorch implementation of our paper "Maria: A Visual Experience Powered Conversational Agent" in ACL 2021.

In this paper, we present Maria, a neural conversation agent powered by the visual world experiences which are retrieved from a large-scale image index. Maria consists of three flexible components, i.e., text-to-image retriever, visual concept detector and visual-knowledge-grounded response generator.

Coming soon!

Summary

Dependencies

  • python 3.7

  • pytorch 1.4.0

  • Ubuntu 18.04

Usage

Text-to-Image Retrieval Model

Please refer to retrieval_model/README.md

Bottom-up Detector Model

Please refer to detector_model/README.md

Dialog Generation Model

Please refer to dialog_model/README.md

Citation

If you find this paper helps your research, please kindly consider citing our paper in your publications.

@inproceedings{liang2021maria,
   title={Maria: A Visual Experience Powered Conversational Agent},
   author={Liang, Zujie and Hu, Huang and Xu, Can and Chongyang, Tao and Geng, Xiubo and Chen, Danqi and Liang, Fan and Jiang, Daxin},
   booktitle={Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL)},
   year={2021}
}

Acknowledgment

Special thanks to the authors of OSCAR, vokenization, and py-bottom-up-attention.

Owner
Jokie
Research Intern @Microsoft
Jokie
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