Remove Artificial Intelligence Remove Data Scarcity Remove ML
article thumbnail

The “Zero-Shot” Mirage: How Data Scarcity Limits Multimodal AI

Marktechpost

Don’t Forget to join our 40k+ ML SubReddit The post The “Zero-Shot” Mirage: How Data Scarcity Limits Multimodal AI appeared first on MarkTechPost. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

article thumbnail

Brown University Researchers Propose LexC-Gen: A New Artificial Intelligence Method that Generates Low-Resource-Language Classification Task Data at Scale

Marktechpost

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. Check out the Paper. All credit for this research goes to the researchers of this project.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

NeoBERT: Modernizing Encoder Models for Enhanced Language Understanding

Marktechpost

Data Scarcity: Pre-training on small datasets (e.g., Also,feel free to follow us on Twitter and dont forget to join our 80k+ ML SubReddit. While newer models like GTE and CDE improved fine-tuning strategies for tasks like retrieval, they rely on outdated backbone architectures inherited from BERT.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 75
article thumbnail

Open Artificial Knowledge (OAK) Dataset: A Large-Scale Resource for AI Research Derived from Wikipedia’s Main Categories

Marktechpost

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has highlighted the critical need for large, diverse, and high-quality datasets to train and evaluate foundation models. OAK dataset offers a comprehensive resource for AI research, derived from Wikipedia’s main categories.

article thumbnail

This paper from Google DeepMind Provides an Overview of Synthetic Data Research, Discussing Its Applications, Challenges, and Future Directions

Marktechpost

In the rapidly evolving landscape of artificial intelligence (AI), the quest for large, diverse, and high-quality datasets represents a significant hurdle. Don’t Forget to join our 40k+ ML SubReddit Want to get in front of 1.5 Also, don’t forget to follow us on Twitter. If you like our work, you will love our newsletter.

article thumbnail

Meet Swin3D++: An Enhanced AI Architecture based on Swin3D for Efficient Pretraining on Multi-Source 3D Point Clouds

Marktechpost

However, the scarcity and limited annotation of 3D data present significant challenges for the development and impact of 3D pretraining. One straightforward solution to address the data scarcity issue is to merge multiple existing 3D datasets and employ the combined data for universal 3D backbone pretraining.

article thumbnail

Boosting Classification Accuracy: Integrating Transfer Learning and Data Augmentation for Enhanced Machine Learning Performance

Marktechpost

Together, these techniques mitigate the issues of limited target data, improving the model’s adaptability and accuracy. A recent paper published by a Chinese research team proposes a novel approach to combat data scarcity in classification tasks within target domains. Check out the Paper.