25 citations · 57 across the 4 of their papers we have counts for
8 papers
UniT: Unified Multimodal Chain-of-Thought Test-time Scaling
Leon Liangyu Chen, Haoyu Ma, Zhipeng Fan +11
Unified models can handle both multimodal understanding and generation within a single architecture, yet they typically operate in a single pass without iteratively refining their…
Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
Xin Xiao, Bohong Wu, Jiacong Wang +3
Existing image-text modality alignment in Vision Language Models (VLMs) treats each text token equally in an autoregressive manner. Despite being simple and effective, this method…
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen, Bo Li, Sheng Shen +5
Visual reasoning requires multimodal perception and commonsense cognition of the world. Recently, multiple vision-language models (VLMs) have been proposed with excellent commonsen…
Improved Baselines with Visual Instruction Tuning
Haotian Liu, Chunyuan Li, Yuheng Li +1
Large multimodal models (LMM) have recently shown encouraging progress with visual instruction tuning. In this note, we show that the fully-connected vision-language cross-modal co…
HallE-Control: Controlling Object Hallucination in Large Multimodal Models
Bohan Zhai, Shijia Yang, Chenfeng Xu +4
Current Large Multimodal Models (LMMs) achieve remarkable progress, yet there remains significant uncertainty regarding their ability to accurately apprehend visual details, that i…
Aligning Large Multimodal Models with Factually Augmented RLHF
Zhiqing Sun, Sheng Shen, Shengcao Cao +9
Large Multimodal Models (LMM) are built across modalities and the misalignment between two modalities can result in "hallucination", generating textual outputs that are not grounde…