7 papers
Implicit Causal Graph Construction in Text via Chain Discovery
Liesbeth Allein, Marie-Francine Moens
Causal graphs in text are typically populated by observable, predefined events. In contrast, we study implicit causal graph construction from text by treating each described cause-…
Protecting multimodal large language models against misleading visualizations
Jonathan Tonglet, Tinne Tuytelaars, Marie-Francine Moens +1
Visualizations play a pivotal role in daily communication in an increasingly data-driven world. Research on multimodal large language models (MLLMs) for automated chart understandi…
NewsRECON: News article REtrieval for image CONtextualization
Jonathan Tonglet, Iryna Gurevych, Tinne Tuytelaars +1
Identifying when and where a news image was taken is crucial for journalists and forensic experts to produce credible stories and debunk misinformation. While many existing methods…
Fast-and-Frugal Text-Graph Transformers are Effective Link Predictors
Andrei C. Coman, Christos Theodoropoulos, Marie-Francine Moens +1
We propose Fast-and-Frugal Text-Graph (FnF-TG) Transformers, a Transformer-based framework that unifies textual and structural information for inductive link prediction in text-att…
Reduction of Supervision for Biomedical Knowledge Discovery
Christos Theodoropoulos, Andrei Catalin Coman, James Henderson +1
Knowledge discovery is hindered by the increasing volume of publications and the scarcity of extensive annotated data. To tackle the challenge of information overload, it is essent…
Towards More Accurate Personalized Image Generation: Addressing Overfitting and Evaluation Bias
Mingxiao Li, Tingyu Qu, Tinne Tuytelaars +1
Personalized image generation via text prompts has great potential to improve daily life and professional work by facilitating the creation of customized visual content. The aim of…