A survey on non-autoregressive generation for neural machine translation and beyond
Non-autoregressive (NAR) generation, which is first proposed in neural machine translation
(NMT) to speed up inference, has attracted much attention in both machine learning and …
(NMT) to speed up inference, has attracted much attention in both machine learning and …
From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences
T Passali, E Chatzikyriakidis, S Andreadis… - arXiv preprint arXiv …, 2023 - arxiv.org
Long sentences have been a persistent issue in written communication for many years since
they make it challenging for readers to grasp the main points or follow the initial intention of …
they make it challenging for readers to grasp the main points or follow the initial intention of …
Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects--A Survey
Generic text summarization approaches often fail to address the specific intent and needs of
individual users. Recently, scholarly attention has turned to the development of …
individual users. Recently, scholarly attention has turned to the development of …
π-PrimeNovo: An Accurate and Efficient Non-Autoregressive Deep Learning Model for De Novo Peptide Sequencing
Peptide sequencing via tandem mass spectrometry (MS/MS) is fundamental in proteomics
data analysis, playing a pivotal role in unraveling the complex world of proteins within …
data analysis, playing a pivotal role in unraveling the complex world of proteins within …
Hierarchical Latent Alignment for Non-Autoregressive Generation under High Compression Ratio
Non-autoregressive generation has attracted more and more attention due to its fast
decoding speed. Latent alignment objectives, such as CTC, are designed to capture the …
decoding speed. Latent alignment objectives, such as CTC, are designed to capture the …