5 papers
A Large-Scale Multi-Dimensional Empirical Study of LLMs for Conversation Summarization
Weixiao Zhou, Gengyao Li, Xianfu Cheng +3
Despite the significant advancement of LLMs in conversation summarization, their evaluation remains limited by insufficient scenarios, input lengths, and sample sizes. Furthermore,…
Mixture of Disentangled Experts with Missing Modalities for Robust Multimodal Sentiment Analysis
Xiang Li, Xiaoming Zhang, Dezhuang Miao +4
Multimodal Sentiment Analysis (MSA) integrates multiple modalities to infer human sentiment, but real-world noise often leads to missing or corrupted data. However, existing featur…
TF-Mamba: Text-enhanced Fusion Mamba with Missing Modalities for Robust Multimodal Sentiment Analysis
Xiang Li, Xianfu Cheng, Dezhuang Miao +2
Multimodal Sentiment Analysis (MSA) with missing modalities has attracted increasing attention recently. While current Transformer-based methods leverage dense text information to…
What Are They Talking About? A Benchmark of Knowledge-Grounded Discussion Summarization
Weixiao Zhou, Junnan Zhu, Gengyao Li +4
Traditional dialogue summarization primarily focuses on dialogue content, assuming it comprises adequate information for a clear summary. However, this assumption often fails for d…
Hybrid CNN-Mamba Enhancement Network for Robust Multimodal Sentiment Analysis
Xiang Li, Xianfu Cheng, Xiaoming Zhang +1
Multimodal Sentiment Analysis (MSA) with missing modalities has recently attracted increasing attention. Although existing research mainly focuses on designing complex model archit…