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cs.LG2026
Multi-Granularity Sentiment Integration for LLM-Based Multimodal Sentiment Analysis
Shanshan Lin, Yuesheng Wu, Chao Chen +4
Multimodal sentiment analysis (MSA) aims to predict sentiment polarity and intensity from heterogeneous inputs such as text, audio, and vision. While large language models (LLMs) o…
cs.LG2026
BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop
Chao Chen, Xujia Li, Dongsheng Hong +4
The challenges of training and inference in few-shot environments persist in the area of graph representation learning. The quality and quantity of labels are often insufficient du…
cs.LG2026
Explanation-Guided Adversarial Training for Robust and Interpretable Models
Chao Chen, Yanhui Chen, Shanshan Lin +4
Deep neural networks (DNNs) have achieved remarkable performance in many tasks, yet they often behave as opaque black boxes. Explanation-guided learning (EGL) methods steer DNNs us…