168 citations · 711 across the 31 of their papers we have counts for
4 papers · 1 filter
Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs
Monisha Jegadeesan, Sachin Kumar, John Wieting +1
We present a novel technique for zero-shot paraphrase generation. The key contribution is an end-to-end multilingual paraphrasing model that is trained using translated parallel co…
On The Ingredients of an Effective Zero-shot Semantic Parser
Pengcheng Yin, John Wieting, Avirup Sil +1
Semantic parsers map natural language utterances into meaning representations (e.g., programs). Such models are typically bottlenecked by the paucity of training data due to the re…
Paraphrastic Representations at Scale
John Wieting, Kevin Gimpel, Graham Neubig +1
We present a system that allows users to train their own state-of-the-art paraphrastic sentence representations in a variety of languages. We also release trained models for Englis…
CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation
Jonathan H. Clark, Dan Garrette, Iulia Turc +1
Pipelined NLP systems have largely been superseded by end-to-end neural modeling, yet nearly all commonly-used models still require an explicit tokenization step. While recent toke…