143 citations · 673 across the 47 of their papers we have counts for
61 papers
Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
Elias Najarro, Shyam Sudhakaran, Sebastian Risi
Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, d…
Fooling Contrastive Language-Image Pre-trained Models with CLIPMasterPrints
Matthias Freiberger, Peter Kun, Christian Igel +2
Models leveraging both visual and textual data such as Contrastive Language-Image Pre-training (CLIP), are the backbone of many recent advances in artificial intelligence. In this…
Learning to Act through Evolution of Neural Diversity in Random Neural Networks
Joachim Winther Pedersen, Sebastian Risi
Biological nervous systems consist of networks of diverse, sophisticated information processors in the form of neurons of different classes. In most artificial neural networks (ANN…
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
Shyam Sudhakaran, Miguel González-Duque, Claire Glanois +3
Procedural Content Generation (PCG) is a technique to generate complex and diverse environments in an automated way. However, while generating content with PCG methods is often str…
Skill Decision Transformer
Shyam Sudhakaran, Sebastian Risi
Recent work has shown that Large Language Models (LLMs) can be incredibly effective for offline reinforcement learning (RL) by representing the traditional RL problem as a sequence…
Severe Damage Recovery in Evolving Soft Robots through Differentiable Programming
Kazuya Horibe, Kathryn Walker, Rasmus Berg Palm +2
Biological systems are very robust to morphological damage, but artificial systems (robots) are currently not. In this paper we present a system based on neural cellular automata,…