Microsoft Research NLP Projects

This is a list of open-sourced projects Microsoft Research NLP Group involved. (ranked in time order)

Datasets

Title	Description	Related projects
Dialogue Feedback Dataset	100+ Millions of dialogues with corresponding human feedback to learn which one gets better feedback	DialogRPT
Grounded Dialogue Dataset	Dialogues with information grounded in external knowledge, e.g. wikipedia pages	DSTC7, CMR
Reddit Dialogue Dataset	147M conversation-like exchanges extracted from Reddit comment chains over a period spanning from 2005 through 2017	DialoGPT

Papers

Title	Links	Notes	Tags
Dialogue Response Ranking Training with Large-Scale Human Feedback Data	code/model/data, demo	EMNLP 2020	dialog ranking
POINTER: Constrained Text Generation via Insertion-based Generative Pre-training	code, demo	EMNLP 2020	generation
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space	code, demo	EMNLP 2020	generation
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers	code	ACL 2020	parsing, sql
A Recipe for Creating Multimodal Aligned Datasets for Sequential Tasks	code	ACL 2020	multimodal
INSET: Sentence Infilling with INter-SEntential Transformer	code/demo	ACL 2020	generation
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation	code/model/data	ACL 2020	dialog generation
MixingBoard: a Knowledgeable Stylized Integrated Text Generation Platform	code	ACL 2020	dialog generation framework knowledge style
Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention	code/data	CVPR 2019	navigation imitation learning
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading	code/model/data	ACL 2019	knowledge dialog generation
Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling	code	ACL 2019	dialog generation framework
Structuring Latent Spaces for Stylized Response Generation	code/data	EMNLP 2019	style dialog generation
Jointly Optimizing Diversity and Relevance in Neural Response Generation	code/data	NAACL 2019	dialog generation
Towards Content Transfer through Grounded Text Generation	code/data	NAACL 2019	generation knowledge

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Legal Notices

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

Microsoft, Windows, Microsoft Azure and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found at http://go.microsoft.com/fwlink/?LinkID=254653.

Privacy information can be found at https://privacy.microsoft.com/en-us/

Microsoft and any contributors reserve all other rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel or otherwise.