Causal Discovery Task

Causal discovery aims to identify cause-and-effect relationships from observational data, a crucial task for understanding complex systems and enabling effective interventions. Current research focuses on leveraging large language models (LLMs) for causal reasoning, exploring how pre-training data and multi-agent architectures influence their performance, and developing novel algorithms based on optimal transport and fuzzy knowledge to handle diverse data types and limited prior information. These advancements are improving the accuracy and efficiency of causal discovery across various domains, from recommender systems to sentiment analysis and time series data analysis, ultimately enhancing our ability to model and predict real-world phenomena.

Papers

September 16, 2024

Causal Discovery in Recommender Systems: Example and Discussion
Emanuele Cavenaghi, Fabio Stella, Markus Zanker
Recommender System Causal Discovery Causal Graph Causal Pattern Single Example Discussion Paper Recommendation Problem Causal Discovery Task

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 21, 2024

Multi-Agent Causal Discovery Using Large Language Models
Hao Duong Le, Xin Xia, Zhang Chen
Multi Agent Causal Discovery Causal Discovery Task

May 14, 2024

Weakly-supervised causal discovery based on fuzzy knowledge and complex data complementarity
Wenrui Li, Wei Zhang, Qinghao Zhang, Xuegong Zhang, Xiaowo Wang
Causal Discovery Fuzzy Logic Causal Discovery Method Causal Knowledge Causal Discovery Task Complementarity Information

April 17, 2024

Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis
Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan
Sentiment Analysis Implicit Sentiment Causal Direction Sentiment Score Sentence Level Sentiment Causal Discovery Task

October 10, 2023

Discovering Mixtures of Structural Causal Models from Time Series Data
Sumanth Varambally, Yi-An Ma, Rose Yu
Causal Discovery Time Series Data Structural Causal Model Input Mixture Causal Discovery Task

April 28, 2023

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
Emre Kıcıman, Robert Ness, Amit Sharma, Chenhao Tan
Causal Graph Causal Pattern New Frontier Causal Reasoning Causal Discovery Task

September 14, 2022

A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms
Hang Chen, Keqing Du, Xinyu Yang, Chenguang Li
Causal Discovery Causal Discovery Method Requirement Based Roadmap Explanatory Paradigm Causal Discovery Task

May 27, 2022

Fast Causal Orientation Learning in Directed Acyclic Graphs
Ramin Safaeian, Saber Salehkaleybar, Mahmoud Tabandeh
Causal Relationship Directed Acyclic Graph Causal DAG Causal Discovery Task

January 23, 2022

Optimal transport for causal discovery
Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang
Optimal Transport Causal Discovery Causal Direction Causal Discovery Task