5 citations · 10 across the 10 of their papers we have counts for
4 papers · 1 filter
Compatibility Matters: A Framework for Token-Level Teacher Selection in On-Policy Distillation
Stanley Wei, Jiin Woo, Kaan Ozkara +1
On-policy distillation (OPD) has recently been introduced as a promising paradigm for continual learning, where a student policy can be supervised at the token-level. Typically, OP…
How to Train Your Little Dragon: Teaching a Small Language Model to Construct and Refine GPU Optimization Scripts
Annabelle Sujun Tang, Wei Tang, Songyao Jiang +7
Compiler transformations interact, making GPU kernel optimization a search for combinations that preserve the computation while improving performance. We introduce HOW TO TRAIN YOU…
Optimizing Large Language Models with Chained LMOs
Sungyoon Kim, Kaan Ozkara, Youngsuk Park
Muon has motivated a growing family of optimizers that compose multiple matrix normalizations, but these methods remain fragmented and lack a unified perspective. We introduce chai…
Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models
Wenlong Deng, Jiaji Huang, Kaan Ozkara +4
Reward hacking arises when a model improves a proxy reward by exploiting shortcuts rather than solving the intended task. We study this failure mode through the geometry of reinfor…