Search Results for author:
Found 7 papers, 3 papers with code
Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage
Such perspectives are called “frames” in communication research. We study, for the first time, the value of combining lead images and their contextual information with text to identify the frame of a given news article.
A Unified Model for Longitudinal Multi-Modal Multi-View Prediction with Missingness
Medical records often consist of different modalities, such as images, text, and tabular information.
Prompting or Fine-tuning? A Comparative Study of Large Language Models for Taxonomy Construction
Our result reveals the following: (1) Even without explicit training on the dataset, the prompting approach outperforms fine-tuning-based approaches.
MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities
We use metric learning via multi-modal image retrieval, resulting in embeddings that can relate images of different modalities.
Towards Improving the Explainability of Text-based Information Retrieval with Knowledge Graphs
In this paper, we propose a general architecture to incorporate knowledge graphs for XIR in various steps of the retrieval process.
Generative appearance replay for continual unsupervised domain adaptation
In contrast to single-step unsupervised domain adaptation (UDA), continual adaptation to a sequence of domains enables leveraging and consolidation of information from multiple domains.
Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images
Multiple Instance Learning (MIL) methods have become increasingly popular for classifying giga-pixel sized Whole-Slide Images (WSIs) in digital pathology.
