Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
IEEE

Causal Inference in AI Based Decision Support: Beyond Correlation to Causation

Abstract: In the emergent and evolving landscape of artificial intelligence, decision support systems have a vital role in the choice-making functions, right from the health sector to finance. Whereas ...
Microsoft

EconML - Microsoft Research: How To

Causal analysis is used to answer what-if questions. Unlike forecasting, which answers the question of what will happen next if everyone keeps behaving as they have in the past, causal inference ...
IEEE

Federated Experiments: Generative Causal Inference Powered by LLM-Based Agents Simulation and RAG-Based Domain Docking

Abstract: Computational experiments method is an essential tool for analyzing, designing, managing, and integrating complex systems. However, a significant challenge arises in constructing agents with ...
GitHub

causal-falsify: A Python library with algorithms for falsifying unconfoundedness assumption in a composite dataset from multiple sources.

We have implemented three falsification algorithms, which can be used complementarily: Hierarchical Graphical Independence Constraint (HGIC) Test: This test jointly assesses whether unconfoundedness ...