causal abstraction

Causal Foundations of Collective Agency CLeaR 2026 Coarsening Causal DAG Models CLeaR 2026 One Model to Rule Them All: Canonically Gluing Causal Models Along Shared Substructures UAI 2026 Aligning Graphical and Functional Causal Abstractions CLeaR 2025 Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability JMLR 2025 Causal Abstraction Inference under Lossy Representations ICML 2025 Causal Abstraction Learning based on the Semantic Embedding Principle ICML 2025 Combining Causal Models for More Accurate Abstractions of Neural Networks CLeaR 2025 Inducing Causal Structure Applied to Glucose Prediction for T1DM Patients CLeaR 2025 On the Identifiability of Causal Abstractions AISTATS 2025 Causally Abstracted Multi-armed Bandits UAI 2024 Causal Optimal Transport of Abstractions CLeaR 2024 Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations CLeaR 2024 Learning Causal Abstractions of Linear Structural Causal Models UAI 2024 Multi-Granularity Causal Structure Learning AAAI 2024 Neural Causal Abstractions AAAI 2024 pyvene: A Library for Understanding and Improving PyTorch Models via Interventions NAACL 2024 Causal Abstraction for Chain-of-Thought Reasoning in Arithmetic Word Problems EMNLP 2023 Causal Abstraction with Soft Interventions CLeaR 2023 Interpretability at Scale: Identifying Causal Mechanisms in Alpaca NeurIPS 2023 Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions CLeaR 2023 Quantifying Consistency and Information Loss for Causal Abstraction Learning IJCAI 2023 Causal Distillation for Language Models NAACL 2022 Inducing Causal Structure for Interpretable Neural Networks ICML 2022 Neuron Dependency Graphs: A Causal Abstraction of Neural Networks ICML 2022