Time series analysis stands as a focal point within the data mining community, serving as a
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …

Large language models (LLMs), such as ChatGPT, have achieved substantial attention due
to their impressive human language understanding and generation capabilities. Therefore …

The scarcity of data presents a critical obstacle to the efficacy of medical vision-language pre-
training (VLP). A potential solution lies in the combination of datasets from various language …

This work summarizes two ways to accomplish Time-Series (TS) tasks in today's Large
Language Model (LLM) context: LLM-for-TS (model-centric) designs and trains a …

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …

Medical vision-language models enable co-learning and integrating features from medical
imaging and clinical text. However, these models are not easy to train and the latent …

Time series forecasting is an essential area of machine learning with a wide range of real-
world applications. Most of the previous forecasting models aim to capture dynamic …

Electron microscopy (EM) images are notoriously challenging to segment due to their
complex structures and lack of effective annotations. Fortunately, large-scale self-supervised …

2Dataset Science Research Institute, Research Institute for Future Medicine, Samsung
Medical Center, Seoul, Republic of Korea dataset. The self-supervision dataset for the LLMs …

Recently, remarkable progress has been made over large language models (LLMs),
demonstrating their unprecedented capability in varieties of natural language tasks …