10 papers · 1 filter
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…
Enhancing Biomedical Knowledge Discovery for Diseases: An Open-Source Framework Applied on Rett Syndrome and Alzheimer's Disease
Christos Theodoropoulos, Andrei Catalin Coman, James Henderson +1
The ever-growing volume of biomedical publications creates a critical need for efficient knowledge discovery. In this context, we introduce an open-source end-to-end framework desi…
End-to-end Planner Training for Language Modeling
Nathan Cornille, Florian Mai, Jingyuan Sun +1
Through end-to-end training to predict the next token, LLMs have become valuable tools for various tasks. Enhancing their core training in language modeling can improve numerous do…