6 papers
SAFE-Cascade: Cost-Adaptive Vision-Language Routing for Chart Question Answering
Ayush Dwivedi, Qixin Wang, Ashvi Soni +5
Vision-language models (VLMs) are powerful for chart question answering, but invoking a VLM for every query can be unnecessarily expensive when many questions are answerable from O…
Leveraging Foundation Models for Causal Generative Modeling
Aneesh Komanduri, Xintao Wu
Causal generative modeling is essential for developing reliable and transparent AI systems capable of counterfactual reasoning. While existing approaches focus on integrating causa…
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…
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…