11 citations · 20 across the 10 of their papers we have counts for
3 papers · 1 filter
A Computationally Feasible Framework for Causal Probabilistic Explanation
Rafal Urbaniak, Sam Witty, Daniel Waxman +7
Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis. Existing tools split into tw…
Hierarchical Experimentalist Agents
Abhranil Chandra, Sankaran Vaidyanathan, Utsav Dhanuka +2
Large language models (LLMs) are increasingly used to act in the real world and augment human decision-making, yet most systems rely on parametric knowledge acquired through imitat…
Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere +3
Reinforcement learning (RL) algorithms often struggle to learn policies that generalize to novel situations due to issues such as causal confusion, overfitting to irrelevant factor…