The prevalent use of benchmarks in current offline reinforcement learnin...
Large Language models (LLMs) have shown remarkable success in assisting ...
Multimodal summarization with multimodal output (MSMO) has emerged as a
...
Self-supervised learning is crucial for clinical imaging applications, g...
The goal of multimodal summarization is to extract the most important
in...
We propose to study and promote the robustness of a model as per its
per...
Recent advancements in Large Language Models (LLMs) have drawn increasin...
Multimodal image-text models have shown remarkable performance in the pa...
One key challenge for multi-task Reinforcement learning (RL) in practice...
Livestream videos have become a significant part of online learning, whe...
Multimedia summarization with multimodal output (MSMO) is a recently exp...
Electroencephalography (EEG) and language have been widely explored
inde...
There has been an increased interest in applying deep neural networks to...
Multimedia summarization with multimodal output can play an essential ro...
In this paper, we focus on a new method of data augmentation to solve th...
In this paper we developed a hierarchical network model, called Hierarch...