Latent Causal Discovery in Reinforcement Learning and Large Language Models
Exploring identifiable latent causal structures to improve decision-making in reinforcement learning and interpretability in large language models.
Exploring identifiable latent causal structures to improve decision-making in reinforcement learning and interpretability in large language models.
This project integrates two recent advances in differentiable DAG learning: (1) analytic DAG constraints for improved computational stability and (2) Truncated Matrix Power …