Fine-grained and Explainable Factuality Evaluation for Multimodal Summarization. - Liqiang Jing; Jingxuan Zuo; Yue Zhang 096 (CoRR, 2024)

Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization. - Yue Zhang 096; Liqiang Jing; Vibhav Gogate (AAAI, 2025)

Can Large Vision-Language Models Understand Multimodal Sarcasm? - Xinyu Wang; Yue Zhang 096; Liqiang Jing (CIKM, 2025)

Tutorial Proposal: Hallucinations in Large Language Models and Large Vision-Language Models. - Liqiang Jing; Yue Zhang 096; Xinya Du (ICMR, 2025)

Can Video Large Multimodal Models Think Like Doubters-or Double-Down: A Study on Defeasible Video Entailment. - Yue Zhang 096; Jilei Sun; Yunhui Guo; Vibhav Gogate (CoRR, 2025)

LOGicalThought: Logic-Based Ontological Grounding of LLMs for High-Assurance Reasoning. - Navapat Nananukul; Yue Zhang 096; Ryan Lee; Eric Boxer; Jonathan May; Vibhav Giridhar Gogate; Jay Pujara; Mayank Kejriwal (CoRR, 2025)

A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding. - Yue Zhang 096; Liqiang Jing; Jia Li; Yapeng Tian; Xinya Du; Yunhui Guo; Vibhav Gogate (CoRR, 2026)