5 papers
Yo'LLaVA: Your Personalized Language and Vision Assistant
Thao Nguyen, Haotian Liu, Yuheng Li +3
Large Multimodal Models (LMMs) have shown remarkable capabilities across a variety of tasks (e.g., image captioning, visual question answering). While broad, their knowledge remain…
Interpolating Video-LLMs: Toward Longer-sequence LMMs in a Training-free Manner
Yuzhang Shang, Bingxin Xu, Weitai Kang +7
Advancements in Large Language Models (LLMs) inspire various strategies for integrating video modalities. A key approach is Video-LLMs, which incorporate an optimizable interface l…
Removing Distributional Discrepancies in Captions Improves Image-Text Alignment
Yuheng Li, Haotian Liu, Mu Cai +5
In this paper, we introduce a model designed to improve the prediction of image-text alignment, targeting the challenge of compositional understanding in current visual-language mo…
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding
Mu Cai, Zeyi Huang, Yuheng Li +3
Large language models (LLMs) have made significant advancements in natural language understanding. However, through that enormous semantic representation that the LLM has learnt, i…
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…