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Found 6 papers, 2 papers with code
Multilingual Universal Sentence Encoder for Semantic Retrieval
We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures.
Universal Sentence Encoder for English
We present easy-to-use TensorFlow Hub sentence embedding models having good task transfer performance.
Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model
A significant roadblock in multilingual neural language modeling is the lack of labeled non-English data.
Learning Semantic Textual Similarity from Conversations
We present a novel approach to learn representations for sentence-level semantic similarity using conversational data.
Universal Sentence Encoder
For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.
Ranked #2 on
Text Classification
on TREC-6
Conversational Response Selection
Semantic Textual Similarity
+7
