Amazon Technologies, Inc.

Ankur Deepak Desai

Bing Xiang

Atul Deo

Andrew Oliver Arnold

Matthew Lee

Srinivas Iragavarapu

Sudipta Sengupta

Ramesh M Nallapati

Parminder Bhatia

Yuchen Tian

Yanitsa Donchev

Praphruetpong Athiwaratkun

Zijian Wang

Rama Krishna Sandeep Pokkunuri

Alexander Johannes Smola

Vamshidhar Krishnamurthy Dantu

Sri Ranga Akhilesh Bontala

Hantian Ding

Wasi Uddin Ahmad

Sathish Arumugam Selvaraj

Ramana Keerthi

Zixuan Lin

Venkat Rakshith Reddy Swamireddy

Lei Gao

Mingyue Shang

Wei Fang

Code completion suggestions may be proactively obtained and validated. An event that triggers obtaining a code completion suggestion for inclusion in a code file being edited using an integrated development environment may be detected. The code completion suggestion may be obtained. The characters of the code completion suggestion may be compared with characters added to the code file after the detection of the event that triggered obtaining the code completion suggestion to determine whether the code completion suggestion is valid. A valid code completion suggestion may then be displayed.

Validating and providing proactively generated code completion suggestions for code development

Evaluation data sets may be programmatically generated for code generation models. An evaluation data set is obtained that includes items that correspond to different evaluation tests for a code generation system. The individual items of the evaluation data set maybe converted, including the conversion of a function signature for the items, the test statements for the items and using a code generation system to generate the body of the function.

Programmatically generating evaluation data sets for code generation models

Pre-fix matching may constrain the generation of next token predictions. Input text to perform a next token prediction may be received. Multiple tokens may be determined from the input text, including a partial token. From possible tokens, one or more matching possible tokens with the partial token may be identified. Next token predictions may then be filtered using the identified possible tokens in order to ensure that the partial token is matched.

Constrained prefix matching for generating next token predictions

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Redmond, WA, United States of America

Ankur Deepak Desai