6 papers
Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
An Vuong, Minh-Hao Van, Chen Zhao +1
AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions. Bilayer 2D material stacking…
Fair In-Context Learning via Latent Concept Variables
Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu +3
The emerging in-context learning (ICL) ability of large language models (LLMs) has prompted their use for predictive tasks in various domains with different data types, including t…
Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction
An Vuong, Minh-Hao Van, Prateek Verma +2
Vision-Language Models (VLMs) have shown strong performance in tasks like visual question answering and multimodal text generation, but their effectiveness in scientific domains su…
Cross-Modal Attention Guided Unlearning in Vision-Language Models
Karuna Bhaila, Aneesh Komanduri, Minh-Hao Van +1
Vision-Language Models (VLMs) have demonstrated immense capabilities in multi-modal understanding and inference tasks such as Visual Question Answering (VQA), which requires models…
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
Minh-Hao Van, Prateek Verma, Chen Zhao +1
Foundation models (FMs) are catalyzing a transformative shift in materials science (MatSci) by enabling scalable, general-purpose, and multimodal AI systems for scientific discover…
Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models
Minh-Hao Van, Xintao Wu
The rapid evolution of social media has provided enhanced communication channels for individuals to create online content, enabling them to express their thoughts and opinions. Mul…