12 citations · 14 across the 9 of their papers we have counts for
5 papers · 1 filter
MSUE: Multi-Modal Soccer Understanding Expert
Litao Li, Yibo Yu, Yufeng Hu +4
This paper presents our solution to the 2026 SoccerNet VQA Challenge. We first develop a cost-effective data synthesis pipeline driven by a Vision-Language Model (VLM), which syste…
Visual Instruction Tuning with Chain of Region-of-Interest
Yixin Chen, Shuai Zhang, Boran Han +1
High-resolution (HR) images are pivotal for enhancing the recognition and understanding capabilities of multimodal large language models (MLLMs). However, directly increasing image…
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Yanwei Li, Yuechen Zhang, Chengyao Wang +5
In this work, we introduce Mini-Gemini, a simple and effective framework enhancing multi-modality Vision Language Models (VLMs). Despite the advancements in VLMs facilitating basic…
CaMML: Context-Aware Multimodal Learner for Large Models
Yixin Chen, Shuai Zhang, Boran Han +2
In this work, we introduce Context-Aware MultiModal Learner (CaMML), for tuning large multimodal models (LMMs). CaMML, a lightweight module, is crafted to seamlessly integrate mult…
Lightweight In-Context Tuning for Multimodal Unified Models
Yixin Chen, Shuai Zhang, Boran Han +1
In-context learning (ICL) involves reasoning from given contextual examples. As more modalities comes, this procedure is becoming more challenging as the interleaved input modaliti…