56 citations · 91 across the 13 of their papers we have counts for
13 papers
Multi-component Causal Tracing in Large Language Models
Zirui Yan, Dennis Wei, Dmitriy A. Katz +2
Causal tracing systematically intervenes on a large language model's (LLM's) internal representations to uncover and quantify the causal pathways linking specific inputs or computa…
Entropic Causal Inference: Graph Identifiability
Spencer Compton, Kristjan Greenewald, Dmitriy Katz +1
Entropic causal inference is a recent framework for learning the causal graph between two variables from observational data by finding the information-theoretically simplest struct…
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
Spencer Compton, Dmitriy Katz, Benjamin Qi +2
Given a set of discrete probability distributions, the minimum entropy coupling is the minimum entropy joint distribution that has the input distributions as its marginals. This ha…
Entropic Causal Inference: Identifiability and Finite Sample Results
Spencer Compton, Murat Kocaoglu, Kristjan Greenewald +1
Entropic causal inference is a framework for inferring the causal direction between two categorical variables from observational data. The central assumption is that the amount of…
Active Structure Learning of Causal DAGs via Directed Clique Tree
Chandler Squires, Sara Magliacane, Kristjan Greenewald +3
A growing body of work has begun to study intervention design for efficient structure learning of causal directed acyclic graphs (DAGs). A typical setting is a causally sufficient…
Size of Interventional Markov Equivalence Classes in Random DAG Models
Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires +1
Directed acyclic graph (DAG) models are popular for capturing causal relationships. From observational and interventional data, a DAG model can only be determined up to its \emph{i…