Structural Causal Model

Structural causal models (SCMs) are a framework for representing causal relationships between variables, aiming to move beyond mere correlation and understand cause-and-effect. Current research focuses on applying SCMs to diverse domains, including multimodal language models, healthcare, and recommendation systems, often employing techniques like backdoor adjustment and counterfactual reasoning to mitigate confounding biases and improve model interpretability. This work is significant because it enables more robust and reliable causal inference, leading to improved decision-making in various fields and a deeper understanding of complex systems. The development of new algorithms for causal discovery and parameter estimation within SCMs, including those leveraging neural networks and graph representations, is a key area of ongoing investigation.

Papers

November 12, 2024

Language Models as Causal Effect Generators
Lucius E.J. Bynum, Kyunghyun Cho
Language Model Causal Inference Causal Structure Causal Model Structural Causal Model Novel Causal Model

November 5, 2024

Causal Responsibility Attribution for Human-AI Collaboration
Yahang Qi, Bernhard Schölkopf, Zhijing Jin
Human Ai Collaboration Structural Causal Model Responsible AI Counterfactual Reasoning Human AI System

October 31, 2024

Identifying General Mechanism Shifts in Linear Causal Representations
Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar
Causal Graph Structural Causal Model Causal Representation Learning Latent Factor Sparse Mechanism

October 28, 2024

Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
Pablo de los Riscos, Fernando Corbacho
Latent Variable Autonomous Robot Causal Model Structural Causal Model Temporal Causal Active Causal

October 27, 2024

DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification
Xiaoxue Han, Huzefa Rangwala, Yue Ning
Graph Neural Network Classification Code Distribution Shift Distribution Generalization Structural Causal Model Real World Graph Self Service CAFE Label Mapping

October 24, 2024

Causal Order Discovery based on Monotonic SCMs
Ali Izadi, Martin Ester
Causal Inference Causal Discovery Structural Causal Model Causal Order

October 17, 2024

Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation
Yikang Chen, Dehui du, Lili Tian
Estimation Task Structural Causal Model Structural Prior Counterfactual Estimation Meaningful Counterfactuals

October 8, 2024

Zero-Shot Learning of Causal Models
Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon
Generative Model Causal Structure Structural Causal Model Generative Process Causal Generative

October 7, 2024

Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality
Guanyu Zhou, Yibo Yan, Xin Zou, Kun Wang, Aiwei Liu, Xuming Hu
Multimodal Large Language Model Causal Inference Structural Causal Model Faulty Negative Mitigation Multimodal Input Causal Attention Modal Prior

October 2, 2024

See Me and Believe Me: Causality and Intersectionality in Testimonial Injustice in Healthcare
Kenya S. Andrews, Mesrob I. Ohannessian, Elena Zheleva
Causal Discovery Healthcare System Causal Pattern Structural Causal Model Intersectional Social Attribute

September 24, 2024

Facing Asymmetry - Uncovering the Causal Link between Facial Symmetry and Expression Classifiers using Synthetic Interventions
Tim Büchner, Niklas Penzel, Orlando Guntinas-Lichius, Joachim Denzler
Black Box Model Causal Relationship Structural Causal Model Expression Classification Asymmetric Crosspoint Element Synthetic Intervention Facial Paralysis

September 16, 2024

The Importance of Causality in Decision Making: A Perspective on Recommender Systems
Emanuele Cavenaghi, Alessio Zanga, Fabio Stella, Markus Zanker
Recommender System Decision Making Causal Graph Visual Perspective Recommendation System Importance Aware Causal Pattern Structural Causal Model Recommendation Algorithm

August 31, 2024

Learning linear acyclic causal model including Gaussian noise using ancestral relationships
Ming Cai, Penggang Gao, Hisayuki Hara
Causal Model Structural Causal Model Gaussian Noise Causal DAG Distributional Invariance

August 1, 2024

Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation
Chu Zhao, Enneng Yang, Yuliang Liang, Pengxiang Lan, Yuting Liu, Jianzhe Zhao, Guibing Guo, Xingwei Wang
Graph Representation Learning Structural Causal Model Graph RepresentAtion

July 24, 2024

On the Parameter Identifiability of Partially Observed Linear Causal Models
Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
Latent Variable Causal Structure Structural Causal Model Parameter Identifiability

July 18, 2024

Latent Causal Probing: A Formal Perspective on Probing with Causal Models of Data
Charles Jin, Martin Rinard
Language Model Raw Data NLP Task Structural Causal Model Linear Probing Underlying Causal Latent Concept

July 17, 2024

On the Complexity of Identification in Linear Structural Causal Models
Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liskiewicz
Person Identification Complexity Matter Structural Causal Model Covariance Matrix Novel Identifiability Test Parameter Identification Causal Parameter

July 12, 2024

Graph Neural Network Causal Explanation via Neural Causal Models
Arman Behnam, Binghui Wang
Graph Neural Network Causal Structure Structural Causal Model Causal Explanation Neural Causal Model GNN Explainers

July 10, 2024

Causal Discovery in Semi-Stationary Time Series
Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu
Causal Discovery Causal Graph Structural Causal Model Causal Relation Non Stationary Time Series

July 8, 2024

Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments
Luka Kovačević, Izzy Newsham, Sach Mukherjee, John Whittaker
Causal Graph Causal Structure Causal Relationship Structural Causal Model Causal Structure Learning Causal Machine Simulation Benchmark Genetic Perturbation

Structural Causal Model

Papers

Language Models as Causal Effect Generators

Causal Responsibility Attribution for Human-AI Collaboration

Identifying General Mechanism Shifts in Linear Causal Representations

Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification

Causal Order Discovery based on Monotonic SCMs

Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation

Zero-Shot Learning of Causal Models

Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality

See Me and Believe Me: Causality and Intersectionality in Testimonial Injustice in Healthcare

Facing Asymmetry - Uncovering the Causal Link between Facial Symmetry and Expression Classifiers using Synthetic Interventions

The Importance of Causality in Decision Making: A Perspective on Recommender Systems

Learning linear acyclic causal model including Gaussian noise using ancestral relationships

Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation

On the Parameter Identifiability of Partially Observed Linear Causal Models

Latent Causal Probing: A Formal Perspective on Probing with Causal Models of Data

On the Complexity of Identification in Linear Structural Causal Models

Graph Neural Network Causal Explanation via Neural Causal Models

Causal Discovery in Semi-Stationary Time Series

Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments