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Found 3 papers, 1 papers with code
GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems
For multi-agent reinforcement learning systems (MARLS), the problem formulation generally involves investing massive reward engineering effort specific to a given problem.
A Mechanistic Analysis of a Transformer Trained on a Symbolic Multi-Step Reasoning Task
We anticipate that the motifs we identified in our synthetic setting can provide valuable insights into the broader operating principles of transformers and thus provide a basis for understanding more complex models.
A Multidimensional Analysis of Social Biases in Vision Transformers
Therefore, we measure the impact of training data, model architecture, and training objectives on social biases in the learned representations of ViTs.
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