414 citations · 723 across the 50 of their papers we have counts for
9 papers · 1 filter
Releasing the Inner Jev: A Simple Recipe for Open Decision Models
Jonathan Geuter, Andrew Cheng, David Alvarez-Melis
LLM-based decision-making systems, also called System One models, have recently gained popularity, most notably through Jev (Almeida, 2026). Given a typed input state, a question,…
Universal Bounds for Self-Normalized Kullback-Leibler Estimation
Buu Phan, Lester Mackey, David Alvarez-Melis
This work studies an entropy-based estimator of Kullback-Leibler (KL) divergence constructed from normalized importance weights. We prove a universal finite-sample bound showing th…
Feeding BabyLMs Macaroni: Code-Switching Curricula Cause Cross-Lingual Convergence
Dries Rooryck, Alex Cai, Yonatan Belinkov +2
Children in multilingual communities often code-switch, using multiple languages in a single utterance. Can we induce cross-lingual alignment in language models by training on code…
Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs
Yan Zhou, Sara Kangaslahti, Jonathan Geuter +4
Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style models---each at multiple sizes…
Domain-Aware Scaling Laws Uncover Data Synergy
Kimia Hamidieh, Lester Mackey, David Alvarez-Melis
Machine learning progress is often attributed to scaling model size and dataset volume, yet the composition of data can be just as consequential. Empirical findings repeatedly show…
Understanding Layer Patching in Model Size Interpolation
Sara Kangaslahti, Jonathan Geuter, Nihal V. Nayak +3
Zero-shot model size interpolation aims to create new models of intermediate target sizes by combining existing models without additional training. Recent work on boomerang distill…