5 papers
User Perception of Attention Visualizations: Effects on Interpretability Across Evidence-Based Medical Documents
Andrés Carvallo, Denis Parra, Peter Brusilovsky +4
The attention mechanism is a core component of the Transformer architecture. Beyond improving performance, attention has been proposed as a mechanism for explainability via attenti…
Exoplanet Transit Candidate Identification in TESS Full-Frame Images via a Transformer-Based Algorithm
Helem Salinas, Rafael Brahm, Greg Olmschenk +4
The Transiting Exoplanet Survey Satellite (TESS) is surveying a large fraction of the sky, generating a vast database of photometric time series data that requires thorough analysi…
EAGLE: Enhanced Visual Grounding Minimizes Hallucinations in Instructional Multimodal Models
Andrés Villa, Juan León Alcázar, Motasem Alfarra +3
Large language models and vision transformers have demonstrated impressive zero-shot capabilities, enabling significant transferability in downstream tasks. The fusion of these mod…
Learning to Route for Dynamic Adapter Composition in Continual Learning with Language Models
Vladimir Araujo, Marie-Francine Moens, Tinne Tuytelaars
Parameter-efficient fine-tuning (PEFT) methods are increasingly used with pre-trained language models (PLMs) for continual learning (CL). These methods typically involve training a…
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based Language Models
Kushal Tatariya, Vladimir Araujo, Thomas Bauwens +1
Pixel-based language models have emerged as a compelling alternative to subword-based language modelling, particularly because they can represent virtually any script. PIXEL, a can…