Saved in:
| Main Authors: | Wang, Siwen, Zhang, Shitou, Chen, Wan-Lin, Truong, Dung, Jung, Tzyy-Ping |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.23042 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
IMU-Enhanced EEG Motion Artifact Removal with Fine-Tuned Large Brain Models
by: Zhang, Yuhong, et al.
Published: (2025)
by: Zhang, Yuhong, et al.
Published: (2025)
Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
by: Fang, Zihan, et al.
Published: (2024)
by: Fang, Zihan, et al.
Published: (2024)
Graph Adapter of EEG Foundation Models for Parameter Efficient Fine Tuning
by: Suzumura, Toyotaro, et al.
Published: (2024)
by: Suzumura, Toyotaro, et al.
Published: (2024)
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
by: Wang, Shumin, et al.
Published: (2026)
by: Wang, Shumin, et al.
Published: (2026)
Preserving Diversity in Supervised Fine-Tuning of Large Language Models
by: Li, Ziniu, et al.
Published: (2024)
by: Li, Ziniu, et al.
Published: (2024)
Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
by: Han, Bing, et al.
Published: (2025)
by: Han, Bing, et al.
Published: (2025)
Stay Tuned: An Empirical Study of the Impact of Hyperparameters on LLM Tuning in Real-World Applications
by: Halfon, Alon, et al.
Published: (2024)
by: Halfon, Alon, et al.
Published: (2024)
KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data
by: Tang, Grace, et al.
Published: (2024)
by: Tang, Grace, et al.
Published: (2024)
Linearization Explains Fine-Tuning in Large Language Models
by: Afzal, Zahra Rahimi, et al.
Published: (2026)
by: Afzal, Zahra Rahimi, et al.
Published: (2026)
TuneComp: Joint Fine-tuning and Compression for Large Foundation Models
by: Chen, Xiangyu, et al.
Published: (2025)
by: Chen, Xiangyu, et al.
Published: (2025)
Fine-Tuning Strategies for Continual Online EEG Motor Imagery Decoding: Insights from a Large-Scale Longitudinal Study
by: Wimpff, Martin, et al.
Published: (2025)
by: Wimpff, Martin, et al.
Published: (2025)
Image-based Novel Fault Detection with Deep Learning Classifiers using Hierarchical Labels
by: Sergin, Nurettin, et al.
Published: (2024)
by: Sergin, Nurettin, et al.
Published: (2024)
Efficient Inference Using Large Language Models with Limited Human Data: Fine-Tuning then Rectification
by: Wang, Lei, et al.
Published: (2025)
by: Wang, Lei, et al.
Published: (2025)
Improving Large Language Models with Concept-Aware Fine-Tuning
by: Chen, Michael K., et al.
Published: (2025)
by: Chen, Michael K., et al.
Published: (2025)
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
by: Zhang, Longteng, et al.
Published: (2026)
by: Zhang, Longteng, et al.
Published: (2026)
Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models
by: Liu, Fengchen, et al.
Published: (2024)
by: Liu, Fengchen, et al.
Published: (2024)
Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler
by: Hu, Zixuan, et al.
Published: (2025)
by: Hu, Zixuan, et al.
Published: (2025)
Benchmarking Time Series Forecasting Models: From Statistical Techniques to Foundation Models in Real-World Applications
by: Arab, Issar, et al.
Published: (2025)
by: Arab, Issar, et al.
Published: (2025)
PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models
by: Agiza, Ahmed, et al.
Published: (2024)
by: Agiza, Ahmed, et al.
Published: (2024)
EEG-Bench: A Benchmark for EEG Foundation Models in Clinical Applications
by: Kastrati, Ard, et al.
Published: (2025)
by: Kastrati, Ard, et al.
Published: (2025)
AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models
by: Liu, Zeyu, et al.
Published: (2024)
by: Liu, Zeyu, et al.
Published: (2024)
Data Difficulty and the Generalization--Extrapolation Tradeoff in LLM Fine-Tuning
by: Liu, Siyuan, et al.
Published: (2026)
by: Liu, Siyuan, et al.
Published: (2026)
Boosting Large Language Models with Mask Fine-Tuning
by: Zhang, Mingyuan, et al.
Published: (2025)
by: Zhang, Mingyuan, et al.
Published: (2025)
Scaling Sparse Fine-Tuning to Large Language Models
by: Ansell, Alan, et al.
Published: (2024)
by: Ansell, Alan, et al.
Published: (2024)
FRoD: Full-Rank Efficient Fine-Tuning with Rotational Degrees for Fast Convergence
by: Wan, Guoan, et al.
Published: (2025)
by: Wan, Guoan, et al.
Published: (2025)
Fine-Tuning is Fine, if Calibrated
by: Mai, Zheda, et al.
Published: (2024)
by: Mai, Zheda, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
by: Wang, Luping, et al.
Published: (2024)
by: Wang, Luping, et al.
Published: (2024)
How Homogenizing the Channel-wise Magnitude Can Enhance EEG Classification Model?
by: Ngo, Huyen, et al.
Published: (2024)
by: Ngo, Huyen, et al.
Published: (2024)
Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting
by: Tran, Trong Khiem, et al.
Published: (2026)
by: Tran, Trong Khiem, et al.
Published: (2026)
QLESS: A Quantized Approach for Data Valuation and Selection in Large Language Model Fine-Tuning
by: Ananta, Moses, et al.
Published: (2025)
by: Ananta, Moses, et al.
Published: (2025)
CatMemo at the FinLLM Challenge Task: Fine-Tuning Large Language Models using Data Fusion in Financial Applications
by: Cao, Yupeng, et al.
Published: (2024)
by: Cao, Yupeng, et al.
Published: (2024)
Artificial Entanglement in the Fine-Tuning of Large Language Models
by: Chen, Min, et al.
Published: (2026)
by: Chen, Min, et al.
Published: (2026)
SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
by: Kim, Gyuhak, et al.
Published: (2025)
by: Kim, Gyuhak, et al.
Published: (2025)
QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models
by: Zhou, Jiajun, et al.
Published: (2025)
by: Zhou, Jiajun, et al.
Published: (2025)
Reinforcement Learning Fine-Tunes a Sparse Subnetwork in Large Language Models
by: Balashov, Andrii
Published: (2025)
by: Balashov, Andrii
Published: (2025)
QuantLRM: Quantization of Large Reasoning Models via Fine-Tuning Signals
by: Zhang, Nan, et al.
Published: (2026)
by: Zhang, Nan, et al.
Published: (2026)
Crafting Efficient Fine-Tuning Strategies for Large Language Models
by: Oliver, Michael, et al.
Published: (2024)
by: Oliver, Michael, et al.
Published: (2024)
Data Normalization Strategies for EEG Deep Learning
by: Truong, Dung, et al.
Published: (2025)
by: Truong, Dung, et al.
Published: (2025)
Enhancing Data Quality in Federated Fine-Tuning of Foundation Models
by: Zhao, Wanru, et al.
Published: (2024)
by: Zhao, Wanru, et al.
Published: (2024)
RobustFSM: Submodular Maximization in Federated Setting with Malicious Clients
by: Tran, Duc A., et al.
Published: (2025)
by: Tran, Duc A., et al.
Published: (2025)
Similar Items
-
IMU-Enhanced EEG Motion Artifact Removal with Fine-Tuned Large Brain Models
by: Zhang, Yuhong, et al.
Published: (2025) -
Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
by: Fang, Zihan, et al.
Published: (2024) -
Graph Adapter of EEG Foundation Models for Parameter Efficient Fine Tuning
by: Suzumura, Toyotaro, et al.
Published: (2024) -
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
by: Wang, Shumin, et al.
Published: (2026) -
Preserving Diversity in Supervised Fine-Tuning of Large Language Models
by: Li, Ziniu, et al.
Published: (2024)