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cs.LG2026
KDFP: A first-principles approach to knowledge distillation in large language models
Ryan Swift, Konstantinos Psounis
Knowledge distillation is an established technique for improving the capabilities of small, efficient student models by training them with the representations of larger, more capab…
cs.LG2026
From Shortcuts to Reasoning: Robust Post-Training of Theory of Mind with Reinforcement Learning
Jike Zhong, Yuxiang Lai, Ming Li +5
Theory of Mind (ToM) is a must-acquire skill for modern foundation model systems to operate effectively and safely in the real world. Recent works have explored honing ToM via post…
cs.LG2025★ 1 cited
SpinML: Customized Synthetic Data Generation for Private Training of Specialized ML Models
Jiang Zhang, Rohan Xavier Sequeira, Konstantinos Psounis
Specialized machine learning (ML) models tailored to users needs and requests are increasingly being deployed on smart devices with cameras, to provide personalized intelligent ser…