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.
Tech Times

NVIDIA Diffusion LLM Hits 2.42x Throughput Without Retraining: Nemotron TwoTower Released

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...
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

Integrating Machine Learning and Observational Causal Inference for Enhanced Spectral and Energy Efficiency in Wireless Networks

Abstract: Ensuring transparency and explainability in Artificial Intelligence (AI)/Machine Learning (ML) models is crucial for their effective deployment in wireless networks. This paper addresses the ...
GitHub

Causal Inference and Discovery in Python

What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...
BMJ

Causal inference in physical activity epidemiology research: an opportunity for better evidence

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
Frontiers

Augmenting large language models with psychologically grounded models of causal reasoning for planning under uncertainty

Large Language Models (LLMs) have come a long way in their ability to solve a wide range of problems. Yet, LLM decision-making still relies primarily on pattern recognition, which may limit its ...
IEEE

Causal Inference via Style Bias Deconfounding for Domain Generalization

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...
VentureBeat

Alembic melted GPUs chasing causal A.I. — now it's running one of the fastest supercomputers in the world

Alembic Technologies has raised $145 million in Series B and growth funding at a valuation 15 times higher than its previous round, betting that the next competitive advantage in artificial ...