Saved in:
| Main Authors: | Tu, Shihao, Zhang, Yupeng, Zhang, Jing, Fu, Zhendong, Zhang, Yin, Yang, Yang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.04057 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the Power of Foundation Models
by: Yuan, Yang
Published: (2022)
by: Yuan, Yang
Published: (2022)
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
by: Zhang, Lei, et al.
Published: (2023)
by: Zhang, Lei, et al.
Published: (2023)
ViTime: Foundation Model for Time Series Forecasting Powered by Vision Intelligence
by: Yang, Luoxiao, et al.
Published: (2024)
by: Yang, Luoxiao, et al.
Published: (2024)
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
by: Liu, Yang, et al.
Published: (2025)
by: Liu, Yang, et al.
Published: (2025)
Navigating the Future of Federated Recommendation Systems with Foundation Models
by: Li, Zhiwei, et al.
Published: (2024)
by: Li, Zhiwei, et al.
Published: (2024)
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
by: Zhang, Weijia, et al.
Published: (2024)
by: Zhang, Weijia, et al.
Published: (2024)
2DXformer: Dual Transformers for Wind Power Forecasting with Dual Exogenous Variables
by: Zhang, Yajuan, et al.
Published: (2025)
by: Zhang, Yajuan, et al.
Published: (2025)
Foundation Model in Biomedicine
by: Liu, Xiangrui, et al.
Published: (2025)
by: Liu, Xiangrui, et al.
Published: (2025)
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting
by: Lu, Jiecheng, et al.
Published: (2025)
by: Lu, Jiecheng, et al.
Published: (2025)
Beacon: Post-Training Quantization with Integrated Grid Selection
by: Zhang, Shihao, et al.
Published: (2025)
by: Zhang, Shihao, et al.
Published: (2025)
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
by: Yuan, Bo, et al.
Published: (2025)
by: Yuan, Bo, et al.
Published: (2025)
A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
by: Li, Zhiwei, et al.
Published: (2025)
by: Li, Zhiwei, et al.
Published: (2025)
HyperMLP: An Integrated Perspective for Sequence Modeling
by: Lu, Jiecheng, et al.
Published: (2026)
by: Lu, Jiecheng, et al.
Published: (2026)
Diversified Scaling Inference in Time Series Foundation Models
by: Hua, Ruijin, et al.
Published: (2026)
by: Hua, Ruijin, et al.
Published: (2026)
The Model Knows, the Decoder Finds: Future Value Guided Particle Power Sampling
by: Nguyen, Tu, et al.
Published: (2026)
by: Nguyen, Tu, et al.
Published: (2026)
Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems
by: Zhang, Hanyu, et al.
Published: (2024)
by: Zhang, Hanyu, et al.
Published: (2024)
Synergies between Federated Foundation Models and Smart Power Grids
by: Hosseinalipour, Seyyedali, et al.
Published: (2025)
by: Hosseinalipour, Seyyedali, et al.
Published: (2025)
On the Expressive Power of Tree-Structured Probabilistic Circuits
by: Yin, Lang, et al.
Published: (2024)
by: Yin, Lang, et al.
Published: (2024)
Conformal Transformations for Symmetric Power Transformers
by: Kumar, Saurabh, et al.
Published: (2025)
by: Kumar, Saurabh, et al.
Published: (2025)
Optimal Power Grid Operations with Foundation Models
by: Puech, Alban, et al.
Published: (2024)
by: Puech, Alban, et al.
Published: (2024)
Are Synthetic Time-series Data Really not as Good as Real Data?
by: Fu, Fanzhe, et al.
Published: (2024)
by: Fu, Fanzhe, et al.
Published: (2024)
When Does Learning Renormalize? Sufficient Conditions for Power Law Spectral Dynamics
by: Zhang, Yizhou
Published: (2025)
by: Zhang, Yizhou
Published: (2025)
AIGS: Generating Science from AI-Powered Automated Falsification
by: Liu, Zijun, et al.
Published: (2024)
by: Liu, Zijun, et al.
Published: (2024)
Foundation Models for the Electric Power Grid
by: Hamann, Hendrik F., et al.
Published: (2024)
by: Hamann, Hendrik F., et al.
Published: (2024)
Muon$^2$: Boosting Muon via Adaptive Second-Moment Preconditioning
by: Liu, Ziyue, et al.
Published: (2026)
by: Liu, Ziyue, et al.
Published: (2026)
A Weather Foundation Model for the Power Grid
by: Bodnar, Cristian, et al.
Published: (2025)
by: Bodnar, Cristian, et al.
Published: (2025)
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
by: Yu, Jun, et al.
Published: (2024)
by: Yu, Jun, et al.
Published: (2024)
CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT
by: Hu, Yi, et al.
Published: (2024)
by: Hu, Yi, et al.
Published: (2024)
Large Language Model-Powered Evolutionary Code Optimization on a Phylogenetic Tree
by: Zhao, Leyi, et al.
Published: (2026)
by: Zhao, Leyi, et al.
Published: (2026)
BSM: Small but Powerful Biological Sequence Model for Genes and Proteins
by: Xiang, Weixi, et al.
Published: (2024)
by: Xiang, Weixi, et al.
Published: (2024)
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
by: Fu, Yali, et al.
Published: (2025)
by: Fu, Yali, et al.
Published: (2025)
Revealing the Power of Masked Autoencoders in Traffic Forecasting
by: Sun, Jiarui, et al.
Published: (2023)
by: Sun, Jiarui, et al.
Published: (2023)
ScatterAD: Temporal-Topological Scattering Mechanism for Time Series Anomaly Detection
by: Yin, Tao, et al.
Published: (2025)
by: Yin, Tao, et al.
Published: (2025)
Power Interpretable Causal ODE Networks: A Unified Model for Explainable Anomaly Detection and Root Cause Analysis in Power Systems
by: Sun, Yue, et al.
Published: (2026)
by: Sun, Yue, et al.
Published: (2026)
Free Energy Mixer
by: Lu, Jiecheng, et al.
Published: (2026)
by: Lu, Jiecheng, et al.
Published: (2026)
Hawk: An Efficient NALM System for Accurate Low-Power Appliance Recognition
by: Wang, Zijian, et al.
Published: (2024)
by: Wang, Zijian, et al.
Published: (2024)
OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
by: Jiang, Dihong, et al.
Published: (2026)
by: Jiang, Dihong, et al.
Published: (2026)
MyGO: Memory Yielding Generative Offline-consolidation for Lifelong Learning Systems
by: Ji, Shihao, et al.
Published: (2025)
by: Ji, Shihao, et al.
Published: (2025)
The Extrapolation Power of Implicit Models
by: Decugis, Juliette, et al.
Published: (2024)
by: Decugis, Juliette, et al.
Published: (2024)
Unlocking the Power of Patch: Patch-Based MLP for Long-Term Time Series Forecasting
by: Tang, Peiwang, et al.
Published: (2024)
by: Tang, Peiwang, et al.
Published: (2024)
Similar Items
-
On the Power of Foundation Models
by: Yuan, Yang
Published: (2022) -
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
by: Zhang, Lei, et al.
Published: (2023) -
ViTime: Foundation Model for Time Series Forecasting Powered by Vision Intelligence
by: Yang, Luoxiao, et al.
Published: (2024) -
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
by: Liu, Yang, et al.
Published: (2025) -
Navigating the Future of Federated Recommendation Systems with Foundation Models
by: Li, Zhiwei, et al.
Published: (2024)