Evaluation and Enhancement of Semantic Grounding in Large
Vision-Language Models

Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models

7 September 2023

Jie Yang

Papers citing "Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models"

7 / 7 papers shown

Title
VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding Jiaqi Wang Yifei Gao Jitao Sang MLLM 103 2 0 24 Nov 2024
Hybrid Primal Sketch: Combining Analogy, Qualitative Representations, and Computer Vision for Scene Understanding Kenneth D. Forbus Kezhen Chen Wangcheng Xu Madeline Usher 30 0 0 05 Jul 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
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Pan Lu Swaroop Mishra Tony Xia Liang Qiu Kai-Wei Chang Song-Chun Zhu Oyvind Tafjord Peter Clark A. Kalyan ELM ReLM LRM 198 1,089 0 20 Sep 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 301 11,730 0 04 Mar 2022
Does Vision-and-Language Pretraining Improve Lexical Grounding? Tian Yun Chen Sun Ellie Pavlick VLM CoGe 32 30 0 21 Sep 2021