:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhao, Qinghua, Gong, Xueling, Chen, Xinyu, Kang, Zhongfeng, Li, Xinlu
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2604.11838
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Beyond Frequency: The Role of Redundancy in Large Language Model Memorization
par: Zhang, Jie, et autres
Publié: (2025)

Rotation-Preserving Supervised Fine-Tuning
par: Jin, Hangzhan, et autres
Publié: (2026)

Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control
par: Wang, Xinyu, et autres
Publié: (2026)

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
par: Roh, Yuji, et autres
Publié: (2024)

Preserving Diversity in Supervised Fine-Tuning of Large Language Models
par: Li, Ziniu, et autres
Publié: (2024)

DeltaDQ: Ultra-High Delta Compression for Fine-Tuned LLMs via Group-wise Dropout and Separate Quantization
par: Jiang, Yanfeng, et autres
Publié: (2024)

Goal-Conditioned Supervised Learning for LLM Fine-Tuning
par: Li, Shijun, et autres
Publié: (2026)

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
par: Wei, Quan, et autres
Publié: (2025)

HELENE: Hessian Layer-wise Clipping and Gradient Annealing for Accelerating Fine-tuning LLM with Zeroth-order Optimization
par: Zhao, Huaqin, et autres
Publié: (2024)

Echo-LoRA: Parameter-Efficient Fine-Tuning via Cross-Layer Representation Injection
par: Peng, Yihang, et autres
Publié: (2026)

Step-wise Adaptive Integration of Supervised Fine-tuning and Reinforcement Learning for Task-Specific LLMs
par: Chen, Jack, et autres
Publié: (2025)

Proximal Supervised Fine-Tuning
par: Zhu, Wenhong, et autres
Publié: (2025)

Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data
par: Rallapalli, Swati, et autres
Publié: (2025)

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning
par: Fu, Yuqian, et autres
Publié: (2025)

ASFT: Aligned Supervised Fine-Tuning through Absolute Likelihood
par: Wang, Ruoyu, et autres
Publié: (2024)

Supervised Fine-Tuning as Inverse Reinforcement Learning
par: Sun, Hao
Publié: (2024)

Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority
par: Shen, Zhanming, et autres
Publié: (2026)

CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning
par: Meng, Fanxu, et autres
Publié: (2024)

Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved)
par: Qin, Chongli, et autres
Publié: (2025)

A Novel Multimodal RUL Framework for Remaining Useful Life Estimation with Layer-wise Explanations
par: Razzaq, Waleed, et autres
Publié: (2025)

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
par: Huang, Zeyu, et autres
Publié: (2025)

Disentangling Recall and Reasoning in Transformer Models through Layer-wise Attention and Activation Analysis
par: Fartale, Harshwardhan, et autres
Publié: (2025)

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
par: Kim, Gyuhak, et autres
Publié: (2025)

Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
par: Ma, Xinyu, et autres
Publié: (2024)

Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity
par: Guo, Wentao, et autres
Publié: (2024)

Parameter-Efficient Fine-Tuning with Circulant and Diagonal Vectors
par: Ding, Xinyu, et autres
Publié: (2025)

Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
par: Ye, Tiandi, et autres
Publié: (2025)

On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
par: Zhang, Wenhao, et autres
Publié: (2025)

Ratio law: mathematical descriptions for a universal relationship between AI performance and input samples
par: Kang, Boming, et autres
Publié: (2024)

LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging
par: Wang, Xinyu, et autres
Publié: (2026)

LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training
par: Gwak, Minju, et autres
Publié: (2026)

The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Models
par: Riemer, Matthew, et autres
Publié: (2025)

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
par: Chen, Xin, et autres
Publié: (2025)

NASH: Neural Architecture and Accelerator Search for Multiplication-Reduced Hybrid Models
par: Xu, Yang, et autres
Publié: (2024)

MallowsPO: Fine-Tune Your LLM with Preference Dispersions
par: Chen, Haoxian, et autres
Publié: (2024)

Resource-efficient Layer-wise Federated Self-supervised Learning
par: Tun, Ye Lin, et autres
Publié: (2024)

Stochastic Layer-wise Learning: Scalable and Efficient Alternative to Backpropagation
par: Yin, Bojian, et autres
Publié: (2025)

Understanding and Guiding Layer Placement in Parameter-Efficient Fine-Tuning of Large Language Models
par: Xu, Yichen, et autres
Publié: (2026)

Alignment Dynamics in LLM Fine-Tuning
par: Huang, Yuhan, et autres
Publié: (2026)

LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
par: Du, Zhekai, et autres
Publié: (2025)