19 citations · 87 across the 26 of their papers we have counts for
5 papers · 1 filter
OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation
Qidong Huang, Xiaoyi Dong, Pan Zhang +6
Hallucination, posed as a pervasive challenge of multi-modal large language models (MLLMs), has significantly impeded their real-world usage that demands precise judgment. Existing…
Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization
Zhiyuan Zhao, Bin Wang, Linke Ouyang +3
Multimodal large language models have made significant advancements in recent years, yet they still suffer from a common issue known as the "hallucination problem", in which the mo…
WanJuan: A Comprehensive Multimodal Dataset for Advancing English and Chinese Large Models
Conghui He, Zhenjiang Jin, Chao Xu +6
The rise in popularity of ChatGPT and GPT-4 has significantly accelerated the development of large models, leading to the creation of numerous impressive large language models(LLMs…
MLLM-DataEngine: An Iterative Refinement Approach for MLLM
Zhiyuan Zhao, Linke Ouyang, Bin Wang +5
Despite the great advance of Multimodal Large Language Models (MLLMs) in both instruction dataset building and benchmarking, the independence of training and evaluation makes curre…
VIGC: Visual Instruction Generation and Correction
Bin Wang, Fan Wu, Xiao Han +8
The integration of visual encoders and large language models (LLMs) has driven recent progress in multimodal large language models (MLLMs). However, the scarcity of high-quality in…