5 papers
SoPE: Spherical Coordinate-Based Positional Embedding for Enhancing Spatial Perception of 3D LVLMs
Guanting Ye, Qiyan Zhao, Wenhao Yu +7
3D Large Vision-Language Models (3D LVLMs) built upon Large Language Models (LLMs) have achieved remarkable progress across various multimodal tasks. However, their inherited posit…
LLMBind: A Unified Modality-Task Integration Framework
Bin Zhu, Munan Ning, Peng Jin +7
Despite recent progress in Multi-Modal Large Language Models (MLLMs), it remains challenging to integrate diverse tasks ranging from pixel-level perception to high-fidelity generat…
LeanPO: Lean Preference Optimization for Likelihood Alignment in Video-LLMs
Xiaodong Wang, Jinfa Huang, Li Yuan +1
Most Video Large Language Models (Video-LLMs) adopt preference alignment techniques, e.g., DPO~\citep{rafailov2024dpo}, to optimize the reward margin between a winning response ($y…
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Bin Lin, Zhenyu Tang, Yang Ye +7
Recent advances demonstrate that scaling Large Vision-Language Models (LVLMs) effectively improves downstream task performances. However, existing scaling methods enable all model…
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
Bin Lin, Yang Ye, Bin Zhu +4
The Large Vision-Language Model (LVLM) has enhanced the performance of various downstream tasks in visual-language understanding. Most existing approaches encode images and videos…