1.3k citations · 2.8k across the 31 of their papers we have counts for
7 papers · 1 filter
PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification
Yinfei Yang, Yuan Zhang, Chris Tar +1
Most existing work on adversarial data generation focuses on English. For example, PAWS (Paraphrase Adversaries from Word Scrambling) consists of challenging English paraphrase ide…
Learning a Multi-Domain Curriculum for Neural Machine Translation
Wei Wang, Ye Tian, Jiquan Ngiam +3
Most data selection research in machine translation focuses on improving a single domain. We perform data selection for multiple domains at once. This is achieved by carefully intr…
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…
ReQA: An Evaluation for End-to-End Answer Retrieval Models
Amin Ahmad, Noah Constant, Yinfei Yang +1
Popular QA benchmarks like SQuAD have driven progress on the task of identifying answer spans within a specific passage, with models now surpassing human performance. However, retr…
Hierarchical Document Encoder for Parallel Corpus Mining
Mandy Guo, Yinfei Yang, Keith Stevens +5
We explore using multilingual document embeddings for nearest neighbor mining of parallel data. Three document-level representations are investigated: (i) document embeddings gener…
Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction
Yinfei Yang, Oshin Agarwal, Chris Tar +2
Modern NLP systems require high-quality annotated data. In specialized domains, expert annotations may be prohibitively expensive. An alternative is to rely on crowdsourcing to red…
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…