8 papers
MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models
Xinjian Zhao, Xiangru Jian, Yaoyao Xu +4
Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representations support property predictio…
FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios
Xiangru Jian, Hao Xu, Wei Pang +13
The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution, yet current evaluations fai…
Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers
Wei Pang, Kevin Qinghong Lin, Xiangru Jian +2
Academic poster generation is a crucial yet challenging task in scientific communication, requiring the compression of long-context interleaved documents into a single, visually co…
The Underappreciated Power of Vision Models for Graph Structural Understanding
Xinjian Zhao, Wei Pang, Zhongkai Xue +6
Graph Neural Networks operate through bottom-up message-passing, fundamentally differing from human visual perception, which intuitively captures global structures first. We invest…
LazyVLM: Neuro-Symbolic Approach to Video Analytics
Xiangru Jian, Wei Pang, Zhengyuan Dong +2
Current video analytics approaches face a fundamental trade-off between flexibility and efficiency. End-to-end Vision Language Models (VLMs) often struggle with long-context proces…
DREAM: Improving Video-Text Retrieval Through Relevance-Based Augmentation Using Large Foundation Models
Yimu Wang, Shuai Yuan, Bo Xue +4
Recent progress in video-text retrieval has been driven largely by advancements in model architectures and training strategies. However, the representation learning capabilities of…