2 papers
cs.LG2026
Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
Adam Ousherovitch, Yixin Wang
Modern learning systems excel at interpolation but struggle to generalize to unseen tasks outside the training distribution's support. This failure occurs even in simple settings,…
cs.LG2026
Compute Aligned Training: Optimizing for Test Time Inference
Adam Ousherovitch, Ambuj Tewari
Scaling test-time compute has emerged as a powerful mechanism for enhancing Large Language Model (LLM) performance. However, standard post-training paradigms, Supervised Fine-Tunin…