6 papers
Distribution Matching Evolutionary Algorithms for Rare Event Sampling
Yonatan Gideoni, Yarin Gal
A novel discovery is one which is both useful and surprising: a generative model's output is a useful discovery if it has a low probability of being generated (it's surprising) and…
Distillation Defenses Easily Break After Reinforcement Learning
Shidan Javaheri, Alexander Panfilov, Oliver Britton +2
Distillation attacks copy the reasoning capabilities of closed-source large language models, allowing bad actors to replicate state-of-the-art performance at low cost. Attackers sy…
Simple Baselines are Competitive with Code Evolution
Yonatan Gideoni, Sebastian Risi, Yarin Gal
Code evolution is a family of techniques that rely on large language models to search through possible computer programs by evolving existing code. While code evolution pipelines h…
Non-invasive Neural Decoding in Source Reconstructed Brain Space
Yonatan Gideoni, Ryan Charles Timms, Oiwi Parker Jones
Non-invasive brainwave decoding is usually done using Magneto/Electroencephalography (MEG/EEG) sensor measurements as inputs. This makes combining datasets and building models with…
Does Double Descent Occur in Self-Supervised Learning?
Alisia Lupidi, Yonatan Gideoni, Dulhan Jayalath
Most investigations into double descent have focused on supervised models while the few works studying self-supervised settings find a surprising lack of the phenomenon. These resu…
Group Invariant Global Pooling
Kamil Bujel, Yonatan Gideoni, Chaitanya K. Joshi +1
Much work has been devoted to devising architectures that build group-equivariant representations, while invariance is often induced using simple global pooling mechanisms. Little…