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cs.LG2026
When Independent Sampling Outperforms Agentic Reasoning
Yihe Dong, Boris Shigida
We study how to allocate inference-time compute for competitive programming under fixed budgets. Evaluating 216 Codeforces problems across Divisions 1-3, we compare agent-based rea…
cs.LG2026
Learning Rate Transfer in Normalized Transformers
Boris Shigida, Boris Hanin, Andrey Gromov
The Normalized Transformer, or nGPT (arXiv:2410.01131) achieves impressive training speedups and does not require weight decay or learning rate warmup. However, despite having hype…
cs.LG2026
The Effect of Mini-Batch Noise on the Implicit Bias of Adam
Matias D. Cattaneo, Boris Shigida
With limited high-quality data and growing compute, multi-epoch training is gaining back its importance across sub-areas of deep learning. Adam(W), versions of which are go-to opti…