Causal View

Causal view research focuses on understanding and leveraging causal relationships within data to improve the reliability and generalizability of machine learning models. Current efforts concentrate on applying causal inference frameworks to various domains, including graph machine learning, natural language processing (using LLMs like BERT and GPT), and medical applications, aiming to mitigate biases and improve model robustness. This work is significant because it addresses limitations of traditional statistical methods that rely solely on correlations, leading to more trustworthy and explainable AI systems with broader applicability across diverse fields.

Papers

November 2, 2024

Marginal Causal Flows for Validation and Inference
Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans
Scientific Inference Causal Discovery Causal Effect External Validation Causal View Unmeasured Confounding Graphical Normalizing Flow

September 15, 2024

A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View
Jing Ma
Timely Survey Distribution Generalization Graph Machine Learning Causal Approach Causal View Graph Generalization

July 24, 2024

Causal modelling without introducing counterfactuals or abstract distributions
Benedikt Höltgen, Robert C. Williamson
Scientific Inference Causal Inference Causal Model High Quality Counterfactuals Causal Event Causal View Multiple Distribution

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

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 View Causal Inference Task Explicitly Mentioned Causal Fact

May 1, 2024

Causal Evaluation of Language Models
Sirui Chen, Bo Peng, Meiqi Chen, Ruiqi Wang, Mengying Xu, Xingyu Zeng, Rui Zhao, Shengjie Zhao, Yu Qiao, Chaochao Lu
Language Model Causal Reasoning Causal View

April 18, 2024

CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state
Xiang Li, Shunpan Liang, Yu Lei, Chen Li, Yulei Hou, Tengfei Ma
Medication Recommendation Causal View Relation Discovery Personalized Treatment Recommendation Drug Embeddings

April 8, 2024

Evaluating Interventional Reasoning Capabilities of Large Language Models
Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar
Causal Inference Causal Reasoning Causal View

March 21, 2024

Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
Speech Presence Structured Dropout Gene Expression Data Causal View Causal Graphical Model Transcriptomic Data Gene Regulatory Neural Network

December 22, 2023

Zero-shot Causal Graph Extrapolation from Text via LLMs
Alessandro Antonucci, Gregorio Piqué, Marco Zaffalon
Large Language Model Text Modality Causal Inference Causal Graph Causal Relation Causal View Ground Truth Causal Zero Shot Causal

July 11, 2023

Reducing Causality to Functions with Structural Models
Tianyi Miao
Causal Pattern Simple Function Multi Scenario Causal Direction Actual Cause Causal View Structure Based Model

May 31, 2023

Unveiling Cross Modality Bias in Visual Question Answering: A Causal View with Possible Worlds VQA
Ali Vosoughi, Shijian Deng, Songyang Zhang, Yapeng Tian, Chenliang Xu, Jiebo Luo
Visual Question Answering 3d Vqa Counterfactual Inference Language Bias VQA System Causal View Visual Bias

May 24, 2023

A Causal View of Entity Bias in (Large) Language Models
Fei Wang, Wenjie Mo, Yiwei Wang, Wenxuan Zhou, Muhao Chen
Language Model Structural Causal Model Causal Intervention Knowledge Conflict Causal View Entity Bias

December 13, 2022

On the Relationship Between Explanation and Prediction: A Causal View
Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
Human Prediction Line by Line Explanation Causal Inference Human Relationship Explanation Method Causal View

July 8, 2022

On the Need and Applicability of Causality for Fair Machine Learning
Rūta Binkytė, Ljupcho Grozdanovski, Sami Zhioua
Procedural Fairness Causal Pattern Community Need Fair Machine Learning Fairness Evaluation Applicability Study Causal Prediction Causal View

June 1, 2022

In the Eye of the Beholder: Robust Prediction with Causal User Modeling
Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
Causal Graph Recommendation System User Behavior Relative Relevance Human Eye Robust Prediction Causal View Relevance Prediction

May 12, 2022

Can counterfactual explanations of AI systems' predictions skew lay users' causal intuitions about the world? If so, can we correct for that?
Marko Tesic, Ulrike Hahn
Human Prediction High Explainability Counterfactual Explanation AI System Causal Relationship User Base Causal View Correlation Graph Causal Concept

March 23, 2022

Can Prompt Probe Pretrained Language Models? Understanding the Invisible Risks from a Causal View
Boxi Cao, Hongyu Lin, Xianpei Han, Fangchao Liu, Le Sun
Language Model Causal Intervention Causal View Hidden Risk Causal Theory

January 31, 2022

Causal Explanations and XAI
Sander Beckers
Counterfactual Explanation Causal Model xAI Community Causal Explanation Causal View

January 10, 2022

Information-Theoretic Bias Reduction via Causal View of Spurious Correlation
Seonguk Seo, Joon-Young Lee, Bohyung Han
Algorithmic Bias Debiasing Framework Causal View