This review discussed the dilemma of small data faced by materials machine learning. First,
we analyzed the limitations brought by small data. Then, the workflow of materials machine …

With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Text recognition is a long-standing research problem for document digitalization. Existing
approaches are usually built based on CNN for image understanding and RNN for char …

In the past few years, the emergence of pre-training models has brought uni-modal fields
such as computer vision (CV) and natural language processing (NLP) to a new era …

Natural language reflects our private lives and identities, making its privacy concerns as
broad as those of real life. Language models lack the ability to understand the context and …

We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual
representations, which we apply to text recognition. To account for the sequence-to …

Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …

Information on social media comprises of various modalities such as textual, visual and
audio. NLP and Computer Vision communities often leverage only one prominent modality …

While GPT-4V (ision) impressively models both visual and textual information
simultaneously, it's hallucination behavior has not been systematically assessed. To bridge …

Research publications are the major repository of scientific knowledge. However, their
unstructured and highly heterogenous format creates a significant obstacle to large-scale …