Existing research of video understanding still struggles to achieve in-depth comprehension
and reasoning in complex videos, primarily due to the under-exploration of two key …

Abstract Text-to-video (T2V) synthesis has gained increasing attention in the community in
which the recently emerged diffusion models (DMs) have promisingly shown stronger …

Abstract Language-image pre-training largely relies on how precisely and thoroughly a text
describes its paired image. In practice, however, the contents of an image can be so rich that …

Recent developments of vision large language models (LLMs) have seen remarkable
progress, yet still encounter challenges towards multimodal generalists, such as coarse …

While existing Aspect-based Sentiment Analysis (ABSA) has received extensive effort and
advancement, there are still gaps in defining a more holistic research target seamlessly …

With advances in the quality of text-to-image (T2I) models has come interest in
benchmarking their prompt faithfulness--the semantic coherence of generated images to the …

This paper describes the architecture of our system developed for Task 3 of SemEval-2024:
Multimodal Emotion-Cause Analysis in Conversations. Our project targets the challenges of …

The realm of aspect-based sentiment analysis (ABSA), which delves into the nuanced
sentiment expressions individuals hold towards specific services or products, has …

The multimodal emotion-cause pair extraction (MECPE) task aims to detect the emotions,
causes, and emotion-cause pairs from multimodal conversations. Existing methods for this …

Event extraction (EE) is a critical direction in the field of information extraction, laying an
important foundation for the construction of structured knowledge bases. EE from text has …