4 papers
Sparsely gated tiny linear experts
Simon Schug
Sparsity allows scaling model parameters without proportionally increasing computational cost. While mixture of experts (MoE) models are made increasingly sparse, individual expert…
Are they human? Detecting large language models by probing human memory constraints
Simon Schug, Brenden M. Lake
The validity of online behavioral research relies on study participants being human rather than machine. In the past, it was possible to detect machines by posing simple challenges…
Scaling can lead to compositional generalization
Florian Redhardt, Yassir Akram, Simon Schug
Can neural networks systematically capture discrete, compositional task structure despite their continuous, distributed nature? The impressive capabilities of large-scale neural ne…
Attention as a Hypernetwork
Simon Schug, Seijin Kobayashi, Yassir Akram +2
Transformers can under some circumstances generalize to novel problem instances whose constituent parts might have been encountered during training, but whose compositions have not…