most citedMultilingual Universal Sentence Encoder for Semantic Retrieval

67 citations · 79 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL201967 cited

Multilingual Universal Sentence Encoder for Semantic Retrieval

Yinfei Yang, Daniel Cer, Amin Ahmad +9

We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures. The models embed text from…

cs.CL201912 cited

Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax

Yinfei Yang, Gustavo Hernandez Abrego, Steve Yuan +6

In this paper, we present an approach to learn multilingual sentence embeddings using a bi-directional dual-encoder with additive margin softmax. The embeddings are able to achieve…

cs.CL2018

Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model

Muthuraman Chidambaram, Yinfei Yang, Daniel Cer +4

A significant roadblock in multilingual neural language modeling is the lack of labeled non-English data. One potential method for overcoming this issue is learning cross-lingual t…

cs.CL2018

Learning Semantic Textual Similarity from Conversations

Yinfei Yang, Steve Yuan, Daniel Cer +7

We present a novel approach to learn representations for sentence-level semantic similarity using conversational data. Our method trains an unsupervised model to predict conversati…

cs.CL2018

Universal Sentence Encoder

Daniel Cer, Yinfei Yang, Sheng-yi Kong +10

We present models for encoding sentences into embedding vectors that specifically target transfer learning to other NLP tasks. The models are efficient and result in accurate perfo…