Hal-Eval: A Universal and Fine-grained Hallucination Evaluation
Framework for Large Vision Language Models

Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models

24 February 2024

Ji Zhang

Papers citing "Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models"

6 / 6 papers shown

Title
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations for Synthetic Videos Zongxia Li Xiyang Wu Yubin Qin Guangyao Shi Hongyang Du Dinesh Manocha Tianyi Zhou Jordan Boyd-Graber MLLM 41 0 0 02 May 2025
Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering Kaixuan Jiang Y. Liu Weixing Chen Jingzhou Luo Ziliang Chen Ling Pan G. Li Liang Lin 51 2 0 14 Mar 2025
HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning Zhecan Wang Garrett Bingham Adams Wei Yu Quoc V. Le Thang Luong Golnaz Ghiasi MLLM LRM 35 9 0 22 Jul 2024
FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback Liqiang Jing Xinya Du 68 17 0 07 Apr 2024
mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality Qinghao Ye Haiyang Xu Guohai Xu Jiabo Ye Ming Yan ... Junfeng Tian Qiang Qi Ji Zhang Feiyan Huang Jingren Zhou VLM MLLM 203 883 0 27 Apr 2023
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts Soravit Changpinyo P. Sharma Nan Ding Radu Soricut VLM 273 1,077 0 17 Feb 2021