:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Chenqi, Liu, Yu, Zhang, Shuo, Denison, Timothy, Zhu, Tingting
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2603.04478
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Survey of Few-Shot Learning for Biomedical Time Series
por: Li, Chenqi, et al.
Publicado: (2024)

AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Representation Space Guided Inversion
por: Li, Chenqi, et al.
Publicado: (2024)

Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models
por: Lu, Cong, et al.
Publicado: (2024)

Standing on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone Detection
por: Khajezade, Mohamad, et al.
Publicado: (2026)

BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
por: Li, Chenqi, et al.
Publicado: (2025)

Strong Teacher Not Needed? On Distillation in LLM Pretraining
por: Lu, Taiming, et al.
Publicado: (2026)

Why does Knowledge Distillation Work? Rethink its Attention and Fidelity Mechanism
por: Guo, Chenqi, et al.
Publicado: (2024)

DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models
por: Wang, Jingyuan, et al.
Publicado: (2026)

Large Cognition Model: Towards Pretrained EEG Foundation Model
por: Chen, Chi-Sheng, et al.
Publicado: (2025)

EEG-DLite: Dataset Distillation for Efficient Large EEG Model Training
por: Tang, Yuting, et al.
Publicado: (2025)

Model Merging via Multi-Teacher Knowledge Distillation
por: Dalili, Seyed Arshan, et al.
Publicado: (2025)

PRISM: Exploring Heterogeneous Pretrained EEG Foundation Model Transfer to Clinical Differential Diagnosis
por: Lahiri, Jeet Bandhu, et al.
Publicado: (2026)

On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
por: Fan, Chenghao, et al.
Publicado: (2024)

NeuroTTT: Bridging Pretraining-Downstream Task Misalignment in EEG Foundation Models via Test-Time Training
por: Wang, Suli, et al.
Publicado: (2025)

Diffusion-Guided Pretraining for Brain Graph Foundation Models
por: Wei, Xinxu, et al.
Publicado: (2026)

Sparse Optimization for Transfer Learning: A L0-Regularized Framework for Multi-Source Domain Adaptation
por: Gong, Chenqi, et al.
Publicado: (2025)

Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
por: Fang, Luyang, et al.
Publicado: (2026)

See Further for Parameter Efficient Fine-tuning by Standing on the Shoulders of Decomposition
por: Si, Chongjie, et al.
Publicado: (2024)

LEAF: Language-EEG Aligned Foundation Model for Brain-Computer Interfaces
por: Jiang, Muyun, et al.
Publicado: (2025)

Pretraining a Foundation Model for Small-Molecule Natural Products
por: Ding, Yuheng, et al.
Publicado: (2025)

REVE: A Foundation Model for EEG -- Adapting to Any Setup with Large-Scale Pretraining on 25,000 Subjects
por: Ouahidi, Yassine El, et al.
Publicado: (2025)

Rethinking the Intermediate Features in Adversarial Attacks: Misleading Robotic Models via Adversarial Distillation
por: Zhao, Ke, et al.
Publicado: (2024)

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model
por: Ma, Jingying, et al.
Publicado: (2025)

From Coefficients to Directions: Rethinking Model Merging with Directional Alignment
por: Chen, Zhikang, et al.
Publicado: (2025)

EEG Foundation Models: Progresses, Benchmarking, and Open Problems
por: Liu, Dingkun, et al.
Publicado: (2026)

Data-Efficient Symbolic Regression via Foundation Model Distillation
por: Ying, Wangyang, et al.
Publicado: (2025)

Self-supervised Pretraining for Decision Foundation Model: Formulation, Pipeline and Challenges
por: Liu, Xiaoqian, et al.
Publicado: (2023)

Towards Generation-Efficient Uncertainty Estimation in Large Language Models
por: Zhu, Mingcheng, et al.
Publicado: (2026)

PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation
por: Ni, Juntong, et al.
Publicado: (2025)

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach
por: Zhu, Yinlin, et al.
Publicado: (2026)

Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation
por: Zhang, Hengyuan, et al.
Publicado: (2025)

STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation
por: Zhang, Chen, et al.
Publicado: (2026)

NovoMolGen: Rethinking Molecular Language Model Pretraining
por: Chitsaz, Kamran, et al.
Publicado: (2025)

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
por: Zhang, Peiyan, et al.
Publicado: (2023)

TaxDistill: Improving Metagenomic Taxonomic Annotation via Distilled Genomic Foundation Models
por: Ye, Rongye, et al.
Publicado: (2026)

Hashing-Baseline: Rethinking Hashing in the Age of Pretrained Models
por: Moummad, Ilyass, et al.
Publicado: (2025)

An Integrated Data Processing Framework for Pretraining Foundation Models
por: Sun, Yiding, et al.
Publicado: (2024)

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation
por: Zhou, Sashuai, et al.
Publicado: (2025)

Why Not Hyperparameter-Friendly Optimisation? A Monotonic Adaptive Norm Rescaling Approach For Long-Tailed Recognition
por: Zhang, Shuo, et al.
Publicado: (2026)

EEG-Bench: A Benchmark for EEG Foundation Models in Clinical Applications
por: Kastrati, Ard, et al.
Publicado: (2025)