Search Results for author:
Found 8 papers, 5 papers with code
Embedding-based Scientific Literature Discovery in a Text Editor Application
Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited.
Character-Level Translation with Self-attention
We explore the suitability of self-attention models for character-level neural machine translation.
Rapformer: Conditional Rap Lyrics Generation with Denoising Autoencoders
The ability to combine symbols to generate language is a defining characteristic of human intelligence, particularly in the context of artistic story-telling through lyrics.
Abstractive Document Summarization without Parallel Data
Abstractive summarization typically relies on large collections of paired articles and summaries.
Summary Refinement through Denoising
We propose a simple method for post-processing the outputs of a text summarization system in order to refine its overall quality.
Large-scale Hierarchical Alignment for Data-driven Text Rewriting
We propose a simple unsupervised method for extracting pseudo-parallel monolingual sentence pairs from comparable corpora representative of two different text styles, such as news articles and scientific papers.
Character-level Chinese-English Translation through ASCII Encoding
Character-level Neural Machine Translation (NMT) models have recently achieved impressive results on many language pairs.
Data-driven Summarization of Scientific Articles
Data-driven approaches to sequence-to-sequence modelling have been successfully applied to short text summarization of news articles.
