Amazon Technologies, Inc.

Walmart Apollo, LLC

Suthee Chaidaroon

Feng Quan Liu

Alessandro Magnani

Min Xie

Xiao Zhang

Jeffrey Thomas Svajlenko

Sidharth Gulati

Regina M Joy

Shruti Subramaniyam

Rick Nayar

Iman Keivanloo

Systems and methods for training and performing query answering for programming related query answering are disclosed. During a training phase, queries and answers of a training dataset may be encoded as vectors into the Euclidean space. Loss values for query-answer pairs, duplicate queries, and augmented queries may be determined using loss functions and may be used to adjust the model of the encoder. During the operation phase, a query may be received and encoded into the Euclidean space. The encoded answer most proximate to the encoded query may be decoded and provided as the most relevant answer.

Neural search for programming-related query answering

A system for retrieving products in response to a customer query includes a computing device configured to obtain query information characterizing a query initiated by the customer on an ecommerce marketplace and to determine embedding-based search results comprising a first list of items. The computing device is also configured to obtain legacy search results comprising a second list of items and to blend the embedding-based search results with the legacy search results to obtain blended search results. The computing device is also configured to send the blended search results to the customer.

Methods and apparatuses for providing search results using embedding-based retrieval

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Sunnyvale, CA, United States of America

Suthee Chaidaroon