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[HTML][HTML] A survey of transformers
Transformers have achieved great success in many artificial intelligence fields, such as
natural language processing, computer vision, and audio processing. Therefore, it is natural …
natural language processing, computer vision, and audio processing. Therefore, it is natural …
Neural machine translation for low-resource languages: A survey
Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …
the early 2000s and has already entered a mature phase. While considered the most widely …
[PDF][PDF] A survey of large language models
Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …
of language intelligence by machine. Language is essentially a complex, intricate system of …
Chatgpt or human? detect and explain. explaining decisions of machine learning model for detecting short chatgpt-generated text
ChatGPT has the ability to generate grammatically flawless and seemingly-human replies to
different types of questions from various domains. The number of its users and of its …
different types of questions from various domains. The number of its users and of its …
On the explainability of natural language processing deep models
Despite their success, deep networks are used as black-box models with outputs that are not
easily explainable during the learning and the prediction phases. This lack of interpretability …
easily explainable during the learning and the prediction phases. This lack of interpretability …
Transformers: State-of-the-art natural language processing
Recent progress in natural language processing has been driven by advances in both
model architecture and model pretraining. Transformer architectures have facilitated …
model architecture and model pretraining. Transformer architectures have facilitated …
Huggingface's transformers: State-of-the-art natural language processing
Recent progress in natural language processing has been driven by advances in both
model architecture and model pretraining. Transformer architectures have facilitated …
model architecture and model pretraining. Transformer architectures have facilitated …
On layer normalization in the transformer architecture
The Transformer is widely used in natural language processing tasks. To train a Transformer
however, one usually needs a carefully designed learning rate warm-up stage, which is …
however, one usually needs a carefully designed learning rate warm-up stage, which is …
Scaling up models and data with t5x and seqio
Scaling up training datasets and model parameters have benefited neural network-based
language models, but also present challenges like distributed compute, input data …
language models, but also present challenges like distributed compute, input data …
A comparative study on transformer vs rnn in speech applications
Sequence-to-sequence models have been widely used in end-to-end speech processing,
for example, automatic speech recognition (ASR), speech translation (ST), and text-to …
for example, automatic speech recognition (ASR), speech translation (ST), and text-to …