75 citations · 132 across the 7 of their papers we have counts for
13 papers
Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature
Katherine Thai, Marzena Karpinska, Kalpesh Krishna +4
Literary translation is a culturally significant task, but it is bottlenecked by the small number of qualified literary translators relative to the many untranslated works publishe…
Faithful to the Document or to the World? Mitigating Hallucinations via Entity-linked Knowledge in Abstractive Summarization
Yue Dong, John Wieting, Pat Verga
Despite recent advances in abstractive summarization, current summarization systems still suffer from content hallucinations where models generate text that is either irrelevant or…
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…
Reformulating Unsupervised Style Transfer as Paraphrase Generation
Kalpesh Krishna, John Wieting, Mohit Iyyer
Modern NLP defines the task of style transfer as modifying the style of a given sentence without appreciably changing its semantics, which implies that the outputs of style transfe…
Improving Candidate Generation for Low-resource Cross-lingual Entity Linking
Shuyan Zhou, Shruti Rijhwani, John Wieting +2
Cross-lingual entity linking (XEL) is the task of finding referents in a target-language knowledge base (KB) for mentions extracted from source-language texts. The first step of (X…