6 papers
Quantifying Overclaiming Propensity in Frontier LLM Agents
Nolan Smyth, Yorguin-Jose Mantilla-Ramos, Pascal Jr Tikeng Notsawo +6
Frontier coding agents are increasingly trusted to work autonomously for long periods of time, yet what they actually did is often hard to tell from their final response. We quanti…
Efficient Safety Alignment of Language Models via Latent Personality Traits
Mohamed Amine Merzouk, Nolan Smyth, Damiano Fornasiere +3
Current safety methods for large language models are known to be vulnerable to adversarial attacks, motivating research into robust alternatives. Latent Adversarial Training (LAT)…
Microlensing Detection and Inference via Learned Bayes Factors
Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh
We present a unified framework for gravitational microlensing event detection and parameter inference. Traditional pipelines use deterministic hard cuts on photometric statistics,…
Transformer Embeddings for Fast Microlensing Inference
Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh
The search for free-floating planets (FFPs) is a key science driver for upcoming microlensing surveys like the Nancy Grace Roman Galactic Exoplanet Survey. These rogue worlds are t…
Neural Deprojection of Galaxy Stellar Mass Profiles
M. J. Yantovski-Barth, Hengyue Zhang, Nolan Smyth +4
We introduce a neural approach to dynamical modeling of galaxies that replaces traditional imaging-based deprojections with a differentiable mapping. Specifically, we train a neura…
Fast Parameter Inference on Pulsar Timing Arrays with Normalizing Flows
David Shih, Marat Freytsis, Stephen R. Taylor +2
Pulsar timing arrays (PTAs) perform Bayesian posterior inference with expensive MCMC methods. Given a dataset of ~10-100 pulsars and O(10^3) timing residuals each, producing a post…