12 citations · 29 across the 9 of their papers we have counts for
7 papers · 1 filter
Rethinking Experience Utilization in Self-Evolving Language Model Agents
Weixiang Zhao, Yingshuo Wang, Yichen Zhang +6
Self-evolving agents improve by accumulating and reusing experience from past interactions. Existing work has largely focused on how experience is constructed, represented, and upd…
Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey
Hao Yang, Yanyan Zhao, Yang Wu +6
Compared to traditional sentiment analysis, which only considers text, multimodal sentiment analysis needs to consider emotional signals from multimodal sources simultaneously and…
An Early Evaluation of GPT-4V(ision)
Yang Wu, Shilong Wang, Hao Yang +4
In this paper, we evaluate different abilities of GPT-4V including visual understanding, language understanding, visual puzzle solving, and understanding of other modalities such a…
Improving Cross-Task Generalization with Step-by-Step Instructions
Yang Wu, Yanyan Zhao, Zhongyang Li +2
Instruction tuning has been shown to be able to improve cross-task generalization of language models. However, it is still challenging for language models to complete the target ta…
An Efficient End-to-End Transformer with Progressive Tri-modal Attention for Multi-modal Emotion Recognition
Yang Wu, Pai Peng, Zhenyu Zhang +2
Recent works on multi-modal emotion recognition move towards end-to-end models, which can extract the task-specific features supervised by the target task compared with the two-pha…
MACSA: A Multimodal Aspect-Category Sentiment Analysis Dataset with Multimodal Fine-grained Aligned Annotations
Hao Yang, Yanyan Zhao, Jianwei Liu +2
Multimodal fine-grained sentiment analysis has recently attracted increasing attention due to its broad applications. However, the existing multimodal fine-grained sentiment datase…
Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors
Yang Wu, Yanyan Zhao, Hao Yang +4
Multimodal sentiment analysis has attracted increasing attention and lots of models have been proposed. However, the performance of the state-of-the-art models decreases sharply wh…