4 papers
Causal Climate Emulation with Bayesian Filtering
Sebastian Hickman, Ilija Trajkovic, Julia Kaltenborn +6
Traditional models of climate change use complex systems of coupled equations to simulate physical processes across the Earth system. These simulations are highly computationally e…
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Y. Rohekar, Yaniv Gurwicz, Sungduk Yu +2
Are generative pre-trained transformer (GPT) models, trained only to predict the next token, implicitly learning a world model from which sequences are generated one token at a tim…
Causal Representation Learning in Temporal Data via Single-Parent Decoding
Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn +6
Scientific research often seeks to understand the causal structure underlying high-level variables in a system. For example, climate scientists study how phenomena, such as El Niñ…
LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models
Gabriela Ben Melech Stan, Estelle Aflalo, Raanan Yehezkel Rohekar +7
In the rapidly evolving landscape of artificial intelligence, multi-modal large language models are emerging as a significant area of interest. These models, which combine various…