2 citations · 5 across the 15 of their papers we have counts for
7 papers · 1 filter
Timestep-Conditioned Transformers for Global Weather Forecasting
Sam Levang, Fran Bartolic, Ty Dickinson +3
Existing machine-learning weather forecasting models rely on predetermined and fixed autoregressive timesteps. The choice of model timestep involves a fundamental trade-off: shorte…
Demonstrating Generalization Failures via Mixtures of Conditional Policies
Jou Barzdukas, Jack Peck, Julian Schulz +3
Post-training of frontier language models is conducted on curated task suites, and inevitably leaves a distribution shift between training and deployment environments. This exposes…
Recursive Scaling in Masked Diffusion Models
Alba Carballo-Castro, Julianna Piskorz, Paulius Rauba +2
Masked diffusion models (MDMs) generate sequences by iteratively refining a partially masked state and committing tokens in parallel. We introduce recursion in MDMs and propose new…
Tiny Autoregressive Recursive Models
Paulius Rauba, Claudio Fanconi, Mihaela van der Schaar
Tiny Recursive Models (TRMs) have recently demonstrated remarkable performance on ARC-AGI, showing that very small models can compete against large foundation models through a two-…
No More, No Less: Least-Privilege Language Models
Paulius Rauba, Dominykas Seputis, Patrikas Vanagas +1
Least privilege is a core security principle: grant each request only the minimum access needed to achieve its goal. Deployed language models almost never follow it, instead being…
Multi-Agent Systems Should be Treated as Principal-Agent Problems
Paulius Rauba, Simonas Cepenas, Mihaela van der Schaar
Consider a multi-agent systems setup in which a principal (a supervisor agent) assigns subtasks to specialized agents and aggregates their responses into a single system-level outp…
Probabilistic Transformers for Joint Modeling of Global Weather Dynamics and Decision-Centric Variables
Paulius Rauba, Viktor Cikojevic, Fran Bartolic +3
Weather forecasts sit upstream of high-stakes decisions in domains such as grid operations, aviation, agriculture, and emergency response. Yet forecast users often face a difficult…