Epistemic Integrity in Large Language Models

1 code implementation • 10 Nov 2024 • Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou, Pratheeksha Nair, Jacob-Junqi Tian, Hikaru Tsujimura, Mayank Goel, Sukanya Krishna, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine

We introduce a new human-labeled dataset and a novel method for measuring the linguistic assertiveness of Large Language Models (LLMs) which cuts error rates by over 50% relative to previous benchmarks.

Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance

1 code implementation • 24 Nov 2021 • Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini

We explore the use of graph-based autoencoders, which operate on jets in their "particle cloud" representations and can leverage the interdependencies among the particles within a jet, for such tasks.

Anomaly Detection Graph Neural Network