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.
ahajournals.org

Appraising the Causal Role of Risk Factors in Coronary Artery Disease and Stroke: A Systematic Review of Mendelian Randomization Studies

Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as ...
IEEE

CauseKG: A Framework Enhancing Causal Inference With Implicit Knowledge Deduced From Knowledge Graphs

Abstract: Causal inference is a critical technique for inferring causal relationships from data and distinguishing causation from correlation. Causal inference frameworks rely on structured data, ...
National Bureau of Economic Research

The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory

We study the causal effects and policy implications of global supply chain disruptions. We construct a new index of supply chain disruptions from the mandatory automatic identification system data of ...
IEEE

CausalABSC: Causal Inference for Aspect Debiasing in Aspect-Based Sentiment Classification

Abstract: As the primary subtask of sentiment analysis, aspect-based sentiment classification (ABSC) aims to predict the sentiment polarity for a given aspect. While recent deep neural models for ABSC ...