Marktechpost

MARCH 3, 2025

Encoder models like BERT and RoBERTa have long been cornerstones of natural language processing (NLP), powering tasks such as text classification, retrieval, and toxicity detection. While newer models like GTE and CDE improved fine-tuning strategies for tasks like retrieval, they rely on outdated backbone architectures inherited from BERT.

BERT 73

BERT Data Scarcity Natural Language Processing Large Language Models 73

Unite.AI

JANUARY 22, 2024

However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity. Different methods, such as rule-based and data-driven approaches, have been proposed to generate synthetic data. Microsoft's PROSE ), employing multilingual BERT models (e.g.,

NLP 173

NLP BERT Data Scarcity Large Language Models 173

Marktechpost

AUGUST 3, 2023

They used the BERT-Score metric to evaluate the diversity of the generated captions. This framework demonstrated higher BERT-Score values, generating captions with more diverse vocabularies. On the other hand, the template-based model exhibits improved performance because it benefits from the musical context present in the template.

Data Scarcity 52

Data Scarcity Large Language Models BERT Natural Language Processing 52

AssemblyAI

SEPTEMBER 22, 2023

Data scarcity: Paired natural anguage descriptions of music and corresponding music recordings are extremely scarce, in contrast to the abundance of image/descriptions pairs available online, e.g. in online art galleries or social media.  This also makes the evaluation step harder and highly subjective.

Convolutional Neural Networks 246

Convolutional Neural Networks AI AI Data Scarcity 246

Pickl AI

OCTOBER 21, 2024

Data Scarcity in Certain Domains While ZSL alleviates some challenges associated with data scarcity, it does not eliminate them entirely—particularly in specialised fields where even related class data may be limited25. Auxiliary information can include semantic attributes (e.g.,

Natural Language Processing 52

Natural Language Processing Data Scarcity Computer Vision Machine Learning 52

deepsense.ai

FEBRUARY 6, 2024

For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. Conclusions The release of the Segment Anything Model has brought about a revolution in addressing data scarcity in image segmentation. Source: [link]. Source: own study.

Prompt Engineering 105

Prompt Engineering Prompt Engineer NLP Computer Vision 105

deepsense.ai

FEBRUARY 12, 2024

For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. Conclusions The release of the Segment Anything Model has brought about a revolution in addressing data scarcity in image segmentation. Source: [link]. Source: own study.

Prompt Engineering 52

Prompt Engineering Prompt Engineer NLP Computer Vision 52