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Yun-Hsuan Sung
Researcher at Google
Publications - 41
Citations - 2936
Yun-Hsuan Sung is an academic researcher from Google. The author has contributed to research in topics: Sentence & Semantic similarity. The author has an hindex of 18, co-authored 35 publications receiving 2142 citations. Previous affiliations of Yun-Hsuan Sung include Stanford University.
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Universal Sentence Encoder
Daniel Cer,Yinfei Yang,Sheng-yi Kong,Nan Hua,Nicole Lyn Untalan Limtiaco,Rhomni St. John,Noah Constant,Mario Guajardo-Cespedes,Steve Yuan,Chris Tar,Yun-Hsuan Sung,Brian Strope,Ray Kurzweil +12 more
TL;DR: It is found that transfer learning using sentence embeddings tends to outperform word level transfer with surprisingly good performance with minimal amounts of supervised training data for a transfer task.
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Efficient Natural Language Response Suggestion for Smart Reply
Matthew L. Henderson,Rami Al-Rfou,Brian Strope,Yun-Hsuan Sung,László Lukács,Ruiqi Guo,Sanjiv Kumar,Balint Miklos,Ray Kurzweil +8 more
TL;DR: A computationally efficient machine-learned method for natural language response suggestion using feed-forward neural networks using n-gram embedding features that achieves the same quality at a small fraction of the computational requirements and latency.
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Multilingual Universal Sentence Encoder for Semantic Retrieval
Yinfei Yang,Daniel Cer,Amin Ahmad,Mandy Guo,Jax Law,Noah Constant,Gustavo Hernandez Abrego,Steve Yuan,Chris Tar,Yun-Hsuan Sung,Brian Strope,Ray Kurzweil +11 more
TL;DR: On transfer learning tasks, the multilingual embeddings approach, and in some cases exceed, the performance of English only sentence embedDings.
Proceedings ArticleDOI
Multilingual Universal Sentence Encoder for Semantic Retrieval
Yinfei Yang,Daniel Cer,Amin Ahmad,Mandy Guo,Jax Law,Noah Constant,Gustavo Hernandez Abrego,Steve Yuan,Chris Tar,Yun-Hsuan Sung,Brian Strope,Ray Kurzweil +11 more
TL;DR: The authors embeds text from 16 languages into a shared semantic space using a multi-task trained dual-encoder that learns tied cross-lingual representations via translation bridge tasks, achieving state-of-the-art performance on both monolingual and crosslingual semantic retrieval tasks.
Proceedings ArticleDOI
Learning Semantic Textual Similarity from Conversations
Yinfei Yang,Steve Yuan,Daniel Cer,Sheng-yi Kong,Noah Constant,Petr Pilar,Heming Ge,Yun-Hsuan Sung,Brian Strope,Ray Kurzweil +9 more
TL;DR: The authors presented a novel approach to learn representations for sentence-level semantic similarity using conversational data, which achieved the best performance among all neural models on the Semantic Textual Similarity (STS) Benchmark and SemEval 2017's Community Question Answering (CQA) question similarity subtask.