Causal Relation

Causal relation research aims to identify and understand cause-and-effect relationships within data, moving beyond simple correlations to reveal underlying mechanisms. Current efforts focus on developing robust algorithms and models, including constraint-based methods, neural networks (like those employing Granger causality or score matching), and large language models (LLMs) for extracting causal information from text and other data sources. These advancements are crucial for various fields, enabling more accurate predictions, improved decision-making in areas like healthcare and policy, and a deeper understanding of complex systems across scientific disciplines. The integration of human expertise and background knowledge is also a growing focus, aiming to improve the reliability and interpretability of causal inferences.

Papers

October 18, 2024

CausalChat: Interactive Causal Model Development and Refinement Using Large Language Models
Yanming Zhang, Akshith Kota, Eric Papenhausen, Klaus Mueller
Causal Model Causal Relation Causal Knowledge Causal Network

October 16, 2024

Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Nelson Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting
System Description Causal Graph Causal Model Causal Relation Causal Knowledge Causal Feature

October 10, 2024

Learning Low-Level Causal Relations using a Simulated Robotic Arm
Miroslav Cibula, Matthias Kerzel, Igor Farkaš
Causal Effect Causal Relation Causal Learning Intelligent Robot Sensorimotor Control

October 8, 2024

Ordering-Based Causal Discovery for Linear and Nonlinear Relations
Zhuopeng Xu, Yujie Li, Cheng Liu, Ning Gui
Causal Discovery Causal Relation Linear Ordered Data Causal Discovery Algorithm Average Causal Effect Topological Ordering

September 20, 2024

Advancing Event Causality Identification via Heuristic Semantic Dependency Inquiry Network
Haoran Li, Qiang Gao, Hongmei Wu, Li Huang
Causal Relation Causal Feature Event Causality Identification Semantic Dependency

September 15, 2024

Causal Inference with Large Language Model: A Survey
Jing Ma
Large Language Model Timely Survey Causal Inference Causal Relation Causal Inference Task

August 31, 2024

WikiCausal: Corpus and Evaluation Framework for Causal Knowledge Graph Construction
Oktie Hassanzadeh
Large Corpus Causal Relation Evaluation Framework Causal Knowledge Causality Extraction

August 29, 2024

Targeted Cause Discovery with Data-Driven Learning
Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun, Hyun Oh Song, Kyunghyun Cho
Causal Relationship Causal Relation Causal Discovery Method Underlying Causal Causal Variable Data Driven Learning

July 29, 2024

From Pre-training Corpora to Large Language Models: What Factors Influence LLM Performance in Causal Discovery Tasks?
Tao Feng, Lizhen Qu, Niket Tandon, Zhuang Li, Xiaoxi Kang, Gholamreza Haffari
Large Corpus Causal Discovery Causal Relation LLM Performance Causal Discovery Task Explicitly Mentioned Causal Fact

July 26, 2024

Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Francesco Montagna, Philipp M. Faller, Patrick Bloebaum, Elke Kirschbaum, Francesco Locatello
Causal Discovery Causal Graph Causal Structure Causal Relation Performance Score Roof Type Data

July 24, 2024

Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning
Tianhang Nan, Yong Ding, Hao Quan, Deliang Li, Lisha Li, Guanghong Zhao, Xiaoyu Cui
Deep Learning Causal Inference Multiple Instance Learning Causal Relation Image Prediction Slide Level Decision Region

July 21, 2024

New Rules for Causal Identification with Background Knowledge
Tian-Zuo Wang, Lue Tao, Zhi-Hua Zhou
Causal Effect Latent Variable Causal Relation Simple RULE Background Knowledge Causal Effect Identification

July 13, 2024

Causality extraction from medical text using Large Language Models (LLMs)
Seethalakshmi Gopalakrishnan, Luciana Garbayo, Wlodek Zadrozny
Large Language Model Causal Relation Medical Text Natural Language Model Causal View Causality Extraction

July 10, 2024

June 18, 2024

LLMs Are Prone to Fallacies in Causal Inference
Nitish Joshi, Abulhair Saparov, Yixin Wang, He He
Medical LLM Causal Inference Causal Relation Causal Inference Task Causal View Explicitly Mentioned Causal Fact

June 4, 2024

On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data
Shunxing Fan, Mingming Gong, Kun Zhang
Causal Discovery Causal Relation Causal Discovery Method Latent Causal

May 23, 2024

Local Causal Discovery for Structural Evidence of Direct Discrimination
Jacqueline Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang
Causal Discovery Structural Causal Model Causal Relation Causal Fairness Direct Discrimination Local Causal Discovery CIViC Evidence

May 15, 2024

DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations
Nima Fathi, Amar Kumar, Brennan Nichyporuk, Mohammad Havaei, Tal Arbel
Counterfactual Explanation Causal Relation Accurate Decoding Counterfactual Image Artifact Detection

April 25, 2024

Evolutionary Causal Discovery with Relative Impact Stratification for Interpretable Data Analysis
Ou Deng, Shoji Nishimura, Atsushi Ogihara, Qun Jin
Causal Discovery Causal Relation Causal Discovery Method Hierarchical Bias Driven Stratification

Causal Relation

Papers

CausalChat: Interactive Causal Model Development and Refinement Using Large Language Models

Systems with Switching Causal Relations: A Meta-Causal Perspective

Learning Low-Level Causal Relations using a Simulated Robotic Arm

Ordering-Based Causal Discovery for Linear and Nonlinear Relations

Advancing Event Causality Identification via Heuristic Semantic Dependency Inquiry Network

Causal Inference with Large Language Model: A Survey

WikiCausal: Corpus and Evaluation Framework for Causal Knowledge Graph Construction

Targeted Cause Discovery with Data-Driven Learning

From Pre-training Corpora to Large Language Models: What Factors Influence LLM Performance in Causal Discovery Tasks?

Score matching through the roof: linear, nonlinear, and latent variables causal discovery

Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning

New Rules for Causal Identification with Background Knowledge

Causality extraction from medical text using Large Language Models (LLMs)

Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding

Causal Discovery in Semi-Stationary Time Series

LLMs Are Prone to Fallacies in Causal Inference

On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data

Local Causal Discovery for Structural Evidence of Direct Discrimination

DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations

Evolutionary Causal Discovery with Relative Impact Stratification for Interpretable Data Analysis