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20242026
most citedEfQAT: An Efficient Framework for Quantization-Aware Training

1 citations · 1 across the 11 of their papers we have counts for

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cs.DS2026

GPTQ-2D: Cubic-Time Two-Sided Adaptive Rounding

Jiale Chen, Torsten Hoefler, Dan Alistarh

Adaptive rounding methods such as GPTQ, or equivalently Babai's nearest plane algorithm, round a real matrix to integers under a quadratic metric. They process the entries in a fix…

cs.LG2026

Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts

Fanny Lehmann, Firat Ozdemir, Yun Cheng +4

While AI weather models excel at short-to-medium range forecasts (up to 15 days), they frequently suffer from ill-defined "instabilities" when rolled out over longer horizons. This…

cs.LG2026

SFT-then-RL Outperforms Mixed-Policy Methods for LLM Reasoning

Alexis Limozin, Eduard Durech, Torsten Hoefler +2

Recent mixed-policy optimization methods for LLM reasoning that interleave or blend supervised and reinforcement learning signals report improvements over the standard SFT-then-RL…

physics.ao-ph2026

Earth System Foundation Model (ESFM): A unified framework for heterogeneous data integration and forecasting

Firat Ozdemir, Yun Cheng, Salman Mohebi +11

Foundation models (FMs) for the Earth system learn statistical relationships between physical variables across massive datasets to enable versatile downstream applications through…

cs.DC2026

An Engineering Journey Training Large Language Models at Scale on Alps: The Apertus Experience

Jonathan Coles, Stefano Schuppli, Lukas Drescher +20

Large Language Models (LLMs) have surged as a transformative technology for science and society, prompting governments worldwide to pursue sovereign AI capabilities that ensure dat…