VIGOR+: LLM-Driven Confounder Generation and Validation
Published:Dec 22, 2025 12:48
•1 min read
•ArXiv
Analysis
The paper likely introduces a novel method for identifying and validating confounders in causal inference using a Large Language Model (LLM) within a feedback loop. The iterative approach, likely involving a CEVAE (Conditional Ensemble Variational Autoencoder), suggests an attempt to improve robustness and accuracy in identifying confounding variables.
Key Takeaways
Reference
“The paper is available on ArXiv.”