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cs.LG2026
RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training
Rachit Bansal, Clara Mohri, Tian Qin +2
The standard LLM training pipeline applies reinforcement learning (RL) only after pre-training and supervised fine-tuning (SFT). We question this status quo by training a LLM from…
cs.LG2026
Cost-Aware Learning
Clara Mohri, Amir Globerson, Haim Kaplan +2
We consider the problem of Cost-Aware Learning, where sampling different components of a finite-sum objective incurs different costs. The objective is to reach a target error while…
cs.SE2026
GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon
Arya Tschand, Chenyu Wang, Zishen Wan +21
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. Thi…