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#Visual Grounding

Beyond Unimodal Shortcuts: MLLMs as Cross-Modal Reasoners for Grounded Named Entity Recognition

Intermediate

Jinlong Ma, Yu Zhang et al.Feb 4arXiv

The paper teaches multimodal large language models (MLLMs) to stop guessing from just text or just images and instead check both together before answering.

#GMNER#Multimodal Large Language Models#Modality Bias

Youtu-VL: Unleashing Visual Potential via Unified Vision-Language Supervision

Intermediate

Zhixiang Wei, Yi Li et al.Jan 27arXiv

Youtu-VL is a new kind of vision-language model that learns to predict both words and tiny image pieces, not just words.

#Vision-Language Models#Unified Autoregressive Supervision#Visual Tokenization

VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents

Intermediate

Zirui Wang, Junyi Zhang et al.Jan 23arXiv

VisGym is a playground of 17 very different visual tasks that test and train AI models that see and talk (Vision–Language Models) to act over many steps.

#VisGym#Vision–Language Models#Multimodal Agents

CPPO: Contrastive Perception for Vision Language Policy Optimization

Intermediate

Ahmad Rezaei, Mohsen Gholami et al.Jan 1arXiv

CPPO is a new way to fine‑tune vision‑language models so they see pictures more accurately before they start to reason.

#CPPO#Contrastive Perception Loss#Vision-Language Models