2 papers
cs.LG2024
Evolution of SAE Features Across Layers in LLMs
Daniel Balcells, Benjamin Lerner, Michael Oesterle +2
Sparse Autoencoders for transformer-based language models are typically defined independently per layer. In this work we analyze statistical relationships between features in adjac…
cs.MA2024
GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems
Ashish Rana, Michael Oesterle, Jannik Brinkmann
For multi-agent reinforcement learning systems (MARLS), the problem formulation generally involves investing massive reward engineering effort specific to a given problem. However,…