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Published Date

Group

Microsoft Research Special Projects

The Microsoft Research Special Projects group operates on the boundary between engineering and research to drive breakthrough innovation. We are a research group with world-class specialists solving highly uncertain, complex problems. We build technologies to…

Publication

RACE: Retrieval-augmented Commit Message Generation

Ensheng Shi, Yanlin Wang, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, Hongbin Sun

The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP’22) | December 2022

Publication

“It would work for me too”: How Online Communities Shape Software Developers’ Trust in AI-Powered Code Generation Tools

Ruijia Cheng, Ruotong Wang, Tom Zimmermann, Denae Ford

December 2022

Publication

Neurosymbolic Repair for Low-Code Formula Languages

Rohan Bavishi, Harshit Joshi, José Cambronero, Anna Fariha, Sumit Gulwani, Vu Le, Ivan Radicek, Ashish Tiwari

OOPSLA | December 2022

Publication

Personalized Action Suggestions in Low-Code Automation Platforms

Saksham Gupta, Gust Verbruggen, Mukul Singh, Sumit Gulwani, Vu Le

International Conference on Software Engineering (ICSE) 2023 – Industry Track | December 2022

Publication

Fault-Aware Neural Code Rankers

Jeevana Priya Inala, Chenglong Wang, Mei Yang, Andres Codas, Mark Encarnación, Shuvendu Lahiri, Madan Musuvathi, Jianfeng Gao

NeurIPS 2022 | November 2022

Project

Publication

SciAI4Industry – Solving PDEs for industry-scale problems with deep learning

Philipp Witte, Russell Hewett, Kumar Saurabh, AmirHossein Sojoodi, Ranveer Chandra

November 2022

Project

Publication

The F# Language Design RFCs (F# 7.0)

Don Syme

November 2022

The F# Language is a co-operation between the F# Community including contributors from Microsoft, Microsoft Research and Github. The RFCs for F# 7.0 have been developed by Don Syme, Phillip Carter and others.

Publication

Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers

Zhewei Yao, Xiaoxia Wu, Conglong Li, Connor Holmes, Minjia Zhang, Cheng Li, Yuxiong He

November 2022

Video

Designing AI Systems with Steerable Long-Term Dynamics

November 21, 2022 | Thorsten Joachims

The feedback that users provide through their choices (e.g. clicks, purchases) is one of the most common types of data readily available for training autonomous systems, and it is widely used in online platforms. However,…

01:38:56

Programming languages and software engineering

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