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Text data augmentation for deep learning
Abstract Natural Language Processing (NLP) is one of the most captivating applications of
Deep Learning. In this survey, we consider how the Data Augmentation training strategy can …
Deep Learning. In this survey, we consider how the Data Augmentation training strategy can …
A survey of text watermarking in the era of large language models
Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …
Historically, their capabilities and application scenarios were limited. However, recent …
Bridgedata v2: A dataset for robot learning at scale
We introduce BridgeData V2, a large and diverse dataset of robotic manipulation behaviors
designed to facilitate research in scalable robot learning. BridgeData V2 contains 53,896 …
designed to facilitate research in scalable robot learning. BridgeData V2 contains 53,896 …
BERTopic: Neural topic modeling with a class-based TF-IDF procedure
M Grootendorst - ar** opinions, hence raising the
question of what drives online news consumption. Here we analyse the causal effect of …
question of what drives online news consumption. Here we analyse the causal effect of …
DiffCSE: Difference-based contrastive learning for sentence embeddings
We propose DiffCSE, an unsupervised contrastive learning framework for learning sentence
embeddings. DiffCSE learns sentence embeddings that are sensitive to the difference …
embeddings. DiffCSE learns sentence embeddings that are sensitive to the difference …
On the sentence embeddings from pre-trained language models
Pre-trained contextual representations like BERT have achieved great success in natural
language processing. However, the sentence embeddings from the pre-trained language …
language processing. However, the sentence embeddings from the pre-trained language …
Large pre-trained language models contain human-like biases of what is right and wrong to do
Artificial writing is permeating our lives due to recent advances in large-scale, transformer-
based language models (LMs) such as BERT, GPT-2 and GPT-3. Using them as pre-trained …
based language models (LMs) such as BERT, GPT-2 and GPT-3. Using them as pre-trained …
Whitening sentence representations for better semantics and faster retrieval
Pre-training models such as BERT have achieved great success in many natural language
processing tasks. However, how to obtain better sentence representation through these pre …
processing tasks. However, how to obtain better sentence representation through these pre …