Author: admin
Time series prediction, outlier detection, recommendation systems
TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation
COVID-19 CT Image-Based Classification and Visualization
COVI3D: Automatic COVID-19 CT Image-Based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies Recently many studies have shown the effectiveness of using augmented reality (AR) and virtual reality (VR) in biomedical image analysis. However, they are not automating the COVID level classification process. Additionally, even with the high potential of CT scan imagery… Continue reading COVID-19 CT Image-Based Classification and Visualization
Can Large Language Models Generate High Quality Patent Claims?
Large language models (LLMs) have shown exceptional performance across various text generation tasks but remain under-explored in the patent domain, which offers highly structured and precise language. This paper constructs a dataset to investigate the performance of current LLMs in patent claim generation. Our results demonstrate that generating claims based on patent descriptions outperforms previous… Continue reading Can Large Language Models Generate High Quality Patent Claims?
Data Bias and Time Series Prediction
Image Edit
Approximate Similarity Search in Vector Databases
Abstract: A fundamental problem in modern vector databases is to process approximate similarity queries in high dimensional space. Vector databases become a central research topic with the increasing popularity of large language models. Troubled by the “curse of dimensionality” issue, it has long been questioned whether it is possible to index high-dimensional data effectively and… Continue reading Approximate Similarity Search in Vector Databases
A Case Study on COVID-19
Time series forecasting, as one of the fundamental machine learning areas, has attracted tremendous attentions over recent years. The solutions have evolved from statistical machine learning (ML) methods to deep learning techniques. One emerging sub-field of time series forecasting is individual disease progression forecasting, e.g., predicting individuals’ disease development over a few days (e.g., deteriorating… Continue reading A Case Study on COVID-19
Enhancing Language Models through Improved Pre-Training and Fine-Tuning
Abstract: Language models (LMs) are essential in natural language processing and vision-language modeling. However, several challenges arise in pre-training and fine-tuning of LMs. First, when learning through unsupervised pre-training, information that are semantically irrelevant may negatively affect downstream tasks, leading to negative transfer. Second, cross-modal masked language modeling is often used to learn vision-language associations… Continue reading Enhancing Language Models through Improved Pre-Training and Fine-Tuning