InferenceEvolve: Towards Automated Causal Effect Estimators through Self-Evolving AI

📰 ArXiv cs.AI

InferenceEvolve is a self-evolving AI framework that automates causal effect estimators using large language models

advanced Published 7 Apr 2026

Action Steps

Identify the problem of causal inference and the need for automation
Use large language models to generate initial causal methods
Iteratively refine the methods through an evolutionary framework
Evaluate the performance of the refined methods on benchmarks

Who Needs to Know This

Data scientists and machine learning engineers on a team can benefit from InferenceEvolve as it simplifies the process of choosing appropriate causal inference methods, while researchers can use it to discover new methods

Key Insight

💡 InferenceEvolve can accelerate scientific discovery by automating the process of choosing and refining causal inference methods