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Scene text detection and recognition: The deep learning era
With the rise and development of deep learning, computer vision has been tremendously
transformed and reshaped. As an important research area in computer vision, scene text …
transformed and reshaped. As an important research area in computer vision, scene text …
[HTML][HTML] Progress in neural NLP: modeling, learning, and reasoning
Natural language processing (NLP) is a subfield of artificial intelligence that focuses on
enabling computers to understand and process human languages. In the last five years, we …
enabling computers to understand and process human languages. In the last five years, we …
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
What does it take to create the Babel Fish, a tool that can help individuals translate speech
between any two languages? While recent breakthroughs in text-based models have …
between any two languages? While recent breakthroughs in text-based models have …
Hyporadise: An open baseline for generative speech recognition with large language models
Advancements in deep neural networks have allowed automatic speech recognition (ASR)
systems to attain human parity on several publicly available clean speech datasets …
systems to attain human parity on several publicly available clean speech datasets …
Levenshtein transformer
Modern neural sequence generation models are built to either generate tokens step-by-step
from scratch or (iteratively) modify a sequence of tokens bounded by a fixed length. In this …
from scratch or (iteratively) modify a sequence of tokens bounded by a fixed length. In this …
Achieving human parity on automatic chinese to english news translation
Machine translation has made rapid advances in recent years. Millions of people are using it
today in online translation systems and mobile applications in order to communicate across …
today in online translation systems and mobile applications in order to communicate across …
Deterministic non-autoregressive neural sequence modeling by iterative refinement
We propose a conditional non-autoregressive neural sequence model based on iterative
refinement. The proposed model is designed based on the principles of latent variable …
refinement. The proposed model is designed based on the principles of latent variable …
When a good translation is wrong in context: Context-aware machine translation improves on deixis, ellipsis, and lexical cohesion
Though machine translation errors caused by the lack of context beyond one sentence have
long been acknowledged, the development of context-aware NMT systems is hampered by …
long been acknowledged, the development of context-aware NMT systems is hampered by …
Neural abstractive text summarization with sequence-to-sequence models
In the past few years, neural abstractive text summarization with sequence-to-sequence
(seq2seq) models have gained a lot of popularity. Many interesting techniques have been …
(seq2seq) models have gained a lot of popularity. Many interesting techniques have been …
Deep reinforcement learning for sequence-to-sequence models
In recent times, sequence-to-sequence (seq2seq) models have gained a lot of popularity
and provide state-of-the-art performance in a wide variety of tasks, such as machine …
and provide state-of-the-art performance in a wide variety of tasks, such as machine …