3 papers
cs.LG2025
TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
Léo Grinsztajn, Klemens Flöge, Oscar Key +23
The first tabular foundation model, TabPFN, and its successor TabPFNv2 have impacted tabular AI substantially, with dozens of methods building on it and hundreds of applications ac…
cs.LG2025
TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
Vladyslav Moroshan, Julien Siems, Arber Zela +2
Foundation models for zero-shot time series forecasting face challenges in efficient long-horizon prediction and reproducibility, with existing synthetic-only approaches underperfo…
cs.CL2025
Where to Begin: Efficient Pretraining via Subnetwork Selection and Distillation
Arjun Krishnakumar, Rhea Sanjay Sukthanker, Hannan Javed Mahadik +5
Small Language models (SLMs) offer an efficient and accessible alternative to Large Language Models (LLMs), delivering strong performance while using far fewer resources. We introd…