Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …

The rise in malicious usage of large language models, such as fake content creation and
academic plagiarism, has motivated the development of approaches that identify AI …

Text augmentation is a popular technique in natural language processing (NLP) that has
been shown to improve the performance of various downstream tasks. The goal of text …

We report on methods to create the largest publicly available parallel corpora by crawling
the web, using open source software. We empirically compare alternative methods and …

We frame the task of machine translation evaluation as one of scoring machine translation
output with a sequence-to-sequence paraphraser, conditioned on a human reference. We …

Conditional text generation often requires lexical constraints, ie, which words should or
shouldn't be included in the output text. While the dominant recipe for conditional text …

Lexically-constrained sequence decoding allows for explicit positive or negative phrase-
based constraints to be placed on target output strings in generation tasks such as machine …

Paraphrasing natural language sentences is a multifaceted process: it might involve
replacing individual words or short phrases, local rearrangement of content, or high-level …

Current end-to-end neural conversation models inherently lack the flexibility to impose
semantic control in the response generation process, often resulting in uninteresting …

Paraphrase generation plays an essential role in natural language process (NLP), and it has
many downstream applications. However, training supervised paraphrase models requires …