Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes
Fuente:
arXiv
Saved in:
| Main Authors: | Lehmann, Fanny, Ozdemir, Firat, Soja, Benedikt, Hoefler, Torsten, Mishra, Siddhartha, Schemm, Sebastian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
by: Lehmann, Fanny, et al.
Published: (2026)
by: Lehmann, Fanny, et al.
Published: (2026)
Earth System Foundation Model (ESFM): A unified framework for heterogeneous data integration and forecasting
by: Ozdemir, Firat, et al.
Published: (2026)
by: Ozdemir, Firat, et al.
Published: (2026)
Scaling Laws of Global Weather Models
by: Yu, Yuejiang, et al.
Published: (2026)
by: Yu, Yuejiang, et al.
Published: (2026)
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024)
by: Zhang, Biao, et al.
Published: (2024)
FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models
by: Nath, Pritthijit, et al.
Published: (2025)
by: Nath, Pritthijit, et al.
Published: (2025)
Replacing Tunable Parameters in Weather and Climate Models with State-Dependent Functions using Reinforcement Learning
by: Nath, Pritthijit, et al.
Published: (2026)
by: Nath, Pritthijit, et al.
Published: (2026)
On Finetuning Tabular Foundation Models
by: Rubachev, Ivan, et al.
Published: (2025)
by: Rubachev, Ivan, et al.
Published: (2025)
Lightweight Time Series Data Valuation on Time Series Foundation Models via In-Context Finetuning
by: Wu, Shunyu, et al.
Published: (2025)
by: Wu, Shunyu, et al.
Published: (2025)
EntryPrune: Neural Network Feature Selection using First Impressions
by: Zimmer, Felix, et al.
Published: (2024)
by: Zimmer, Felix, et al.
Published: (2024)
Poseidon: Efficient Foundation Models for PDEs
by: Herde, Maximilian, et al.
Published: (2024)
by: Herde, Maximilian, et al.
Published: (2024)
Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics
by: Bobrin, Maksim, et al.
Published: (2025)
by: Bobrin, Maksim, et al.
Published: (2025)
Building Machine Learning Limited Area Models: Kilometer-Scale Weather Forecasting in Realistic Settings
by: Adamov, Simon, et al.
Published: (2025)
by: Adamov, Simon, et al.
Published: (2025)
Rectified Flows for Fast Multiscale Fluid Flow Modeling
by: Armegioiu, Victor, et al.
Published: (2025)
by: Armegioiu, Victor, et al.
Published: (2025)
Multimodal Web Navigation with Instruction-Finetuned Foundation Models
by: Furuta, Hiroki, et al.
Published: (2023)
by: Furuta, Hiroki, et al.
Published: (2023)
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
by: Qiao, Zhongzheng, et al.
Published: (2025)
by: Qiao, Zhongzheng, et al.
Published: (2025)
Near-Optimal Sparse Allreduce for Distributed Deep Learning
by: Li, Shigang, et al.
Published: (2022)
by: Li, Shigang, et al.
Published: (2022)
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
by: Li, Shigang, et al.
Published: (2021)
by: Li, Shigang, et al.
Published: (2021)
In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
by: Xu, Shangqing, et al.
Published: (2026)
by: Xu, Shangqing, et al.
Published: (2026)
MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
by: Frantar, Elias, et al.
Published: (2024)
by: Frantar, Elias, et al.
Published: (2024)
Multiple-Input Fourier Neural Operator (MIFNO) for source-dependent 3D elastodynamics
by: Lehmann, Fanny, et al.
Published: (2024)
by: Lehmann, Fanny, et al.
Published: (2024)
Fourier Neural Operator Surrogate Model to Predict 3D Seismic Waves Propagation
by: Lehmann, Fanny, et al.
Published: (2023)
by: Lehmann, Fanny, et al.
Published: (2023)
Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks
by: Höhlein, Kevin, et al.
Published: (2023)
by: Höhlein, Kevin, et al.
Published: (2023)
Towards a Certificate of Trust: Task-Aware OOD Detection for Scientific AI
by: Raonić, Bogdan, et al.
Published: (2025)
by: Raonić, Bogdan, et al.
Published: (2025)
Active Model Selection for Large Language Models
by: Durmazkeser, Yavuz, et al.
Published: (2025)
by: Durmazkeser, Yavuz, et al.
Published: (2025)
Federated Prompt Learning for Weather Foundation Models on Devices
by: Chen, Shengchao, et al.
Published: (2023)
by: Chen, Shengchao, et al.
Published: (2023)
Epidemiology of Large Language Models: A Benchmark for Observational Distribution Knowledge
by: Plecko, Drago, et al.
Published: (2025)
by: Plecko, Drago, et al.
Published: (2025)
Grid Games: The Power of Multiple Grids for Quantizing Large Language Models
by: Egiazarian, Vage, et al.
Published: (2026)
by: Egiazarian, Vage, et al.
Published: (2026)
Large Language Model Selection with Limited Annotations
by: Durmazkeser, Yavuz, et al.
Published: (2026)
by: Durmazkeser, Yavuz, et al.
Published: (2026)
Beyond Outliers: A Study of Optimizers Under Quantization
by: Vlassis, Georgios, et al.
Published: (2025)
by: Vlassis, Georgios, et al.
Published: (2025)
EfQAT: An Efficient Framework for Quantization-Aware Training
by: Ashkboos, Saleh, et al.
Published: (2024)
by: Ashkboos, Saleh, et al.
Published: (2024)
Deep Learning and Foundation Models for Weather Prediction: A Survey
by: Shi, Jimeng, et al.
Published: (2025)
by: Shi, Jimeng, et al.
Published: (2025)
Integrating Fourier Neural Operators with Diffusion Models to improve Spectral Representation of Synthetic Earthquake Ground Motion Response
by: Perrone, Niccolò, et al.
Published: (2025)
by: Perrone, Niccolò, et al.
Published: (2025)
All models are wrong, some are useful: Model Selection with Limited Labels
by: Okanovic, Patrik, et al.
Published: (2024)
by: Okanovic, Patrik, et al.
Published: (2024)
Reading the Finetuning Prior: Verbatim Content Recovery via Contrastive Decoding Diffing
by: Brzozowski, Michał, et al.
Published: (2026)
by: Brzozowski, Michał, et al.
Published: (2026)
DaCe AD: Unifying High-Performance Automatic Differentiation for Machine Learning and Scientific Computing
by: Boudaoud, Afif, et al.
Published: (2025)
by: Boudaoud, Afif, et al.
Published: (2025)
Confounder Detection via Treatment Intent: A New Observational Study Design
by: Plecko, Drago, et al.
Published: (2026)
by: Plecko, Drago, et al.
Published: (2026)
SEMPO: Lightweight Foundation Models for Time Series Forecasting
by: He, Hui, et al.
Published: (2025)
by: He, Hui, et al.
Published: (2025)
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning
by: Saha, Pramit, et al.
Published: (2024)
by: Saha, Pramit, et al.
Published: (2024)
A universal approximation theorem for nonlinear resistive networks
by: Scellier, Benjamin, et al.
Published: (2023)
by: Scellier, Benjamin, et al.
Published: (2023)
Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
by: Cao, Shilei, et al.
Published: (2025)
by: Cao, Shilei, et al.
Published: (2025)
Similar Items
-
Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
by: Lehmann, Fanny, et al.
Published: (2026) -
Earth System Foundation Model (ESFM): A unified framework for heterogeneous data integration and forecasting
by: Ozdemir, Firat, et al.
Published: (2026) -
Scaling Laws of Global Weather Models
by: Yu, Yuejiang, et al.
Published: (2026) -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024) -
FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models
by: Nath, Pritthijit, et al.
Published: (2025)