What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration. - Libo Qin 001; Qiguang Chen; Hao Fei 003; Zhi Chen 006; Min Li 007; Wanxiang Che (NeurIPS, 2024)

Divide-Solve-Combine: An Interpretable and Accurate Prompting Framework for Zero-shot Multi-Intent Detection. - Libo Qin 001; Qiguang Chen; Jingxuan Zhou; Jin Wang; Hao Fei 003; Wanxiang Che; Min Li 007 (AAAI, 2025)

CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models. - Zihui Cheng; Qiguang Chen; Jin Zhang; Hao Fei 003; Xiaocheng Feng; Wanxiang Che; Min Li 007; Libo Qin 001 (AAAI, 2025)

CCHall: A Novel Benchmark for Joint Cross-Lingual and Cross-Modal Hallucinations Detection in Large Language Models. - Yongheng Zhang 001; Xu Liu; Ruoxi Zhou; Qiguang Chen; Hao Fei 003; Wenpeng Lu; Libo Qin 001 (ACL (1), 2025)

Visual Thoughts: A Unified Perspective of Understanding Multimodal Chain-of-Thought. - Zihui Cheng; Qiguang Chen; Xiao Xu 005; Jiaqi Wang 012; Weiyun Wang; Hao Fei 003; Yidong Wang; Alex Jinpeng Wang; Zhi Chen 006; Wanxiang Che; Libo Qin 001 (CoRR, 2025)

ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models. - Yongheng Zhang 001; Xu Liu; Ruihan Tao; Qiguang Chen; Hao Fei 003; Wanxiang Che; Libo Qin 001 (CoRR, 2025)