8 papers
Fast and Slow Variational Continual Learning
Subarnaduti Paul, Yohan Jung, Mohammad Emtiyaz Khan +3
Continual learning remains a major challenge for modern deep networks, partly because commonly used optimizers lack inherent mechanisms for continual adaptation. One such natural m…
Position: Modular Memory is the Key to Continual Learning Agents
Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov +21
Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute. Despite surpassing human performance in several domains, these…
Making a Name for Myself: On Academic Naming Policies and their Impact
A Pranav, Vagrant Gautam, Martin Mundt +6
In academic publishing, names connect scholars to their work. When scholars change their names, including for marriage, academic recognition, or gender transition, they may lose cr…
CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models
Niharika Hegde, Subarnaduti Paul, Lars Joel-Frey +4
Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora are diverse, their frequent lack…
Tractable Representation Learning with Probabilistic Circuits
Steven Braun, Sahil Sidheekh, Antonio Vergari +3
Probabilistic circuits (PCs) are powerful probabilistic models that enable exact and tractable inference, making them highly suitable for probabilistic reasoning and inference task…
Aligning Generalisation Between Humans and Machines
Filip Ilievski, Barbara Hammer, Frank van Harmelen +22
Recent advances in AI -- including generative approaches -- have resulted in technology that can support humans in scientific discovery and forming decisions, but may also disrupt…