1 citations · 1 across the 4 of their papers we have counts for
4 papers
DiG-bench: Discovery in Games
Ruairidh M. Battleday, Kai Sandbrink, Jimi Cullen-Drohan +13
Discovery---formulating novel generalizations---is a central part of the scientific process. Despite its importance, there is a gap in the current AI benchmark landscape, with few…
Pretraining Curricula Enable Selective Fine-tuning
Sebastian A. Bruijns, Jirko Rubruck, Mia H. Whitefield +3
Transformers follow implicit curricula whereby some tasks are learned before others. However, how explicit pretraining curricula influence learning, generalization, and the selecti…
Flexible task abstractions emerge in linear networks with fast and bounded units
Kai Sandbrink, Jan P. Bauer, Alexandra M. Proca +3
Animals survive in dynamic environments changing at arbitrary timescales, but such data distribution shifts are a challenge to neural networks. To adapt to change, neural systems m…
Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
Zhonghao He, Jascha Achterberg, Katie Collins +13
As deep learning systems are scaled up to many billions of parameters, relating their internal structure to external behaviors becomes very challenging. Although daunting, this pro…