5 papers
Visual Thoughts: A Unified Perspective of Understanding Multimodal Chain-of-Thought
Zihui Cheng, Qiguang Chen, Xiao Xu +8
Large Vision-Language Models (LVLMs) have achieved significant success in multimodal tasks, with multimodal chain-of-thought (MCoT) further enhancing performance and interpretabili…
ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models
Yongheng Zhang, Xu Liu, Ruihan Tao +4
Video understanding plays a vital role in bridging low-level visual signals with high-level cognitive reasoning, and is fundamental to applications such as autonomous driving, embo…
CCHall: A Novel Benchmark for Joint Cross-Lingual and Cross-Modal Hallucinations Detection in Large Language Models
Yongheng Zhang, Xu Liu, Ruoxi Zhou +4
Investigating hallucination issues in large language models (LLMs) within cross-lingual and cross-modal scenarios can greatly advance the large-scale deployment in real-world appli…
CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models
Zihui Cheng, Qiguang Chen, Jin Zhang +5
Large Vision-Language Models (LVLMs) have recently demonstrated amazing success in multi-modal tasks, including advancements in Multi-modal Chain-of-Thought (MCoT) reasoning. Despi…
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration
Libo Qin, Qiguang Chen, Hao Fei +3
Recently, rapid advancements in Multi-Modal In-Context Learning (MM-ICL) have achieved notable success, which is capable of achieving superior performance across various tasks with…