:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Deng, Jiaxin, Zhu, Qingcheng, Pang, Junbiao, Yang, Linlin, Fu, Zhongqian, Zhang, Baochang
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language
Accès en ligne:	https://arxiv.org/abs/2508.00522
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Bilateral Sharpness-Aware Minimization for Flatter Minima
par: Deng, Jiaxin, et autres
Publié: (2024)

Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization
par: Deng, Jiaxin, et autres
Publié: (2024)

Effective Gradient Sample Size via Variation Estimation for Accelerating Sharpness aware Minimization
par: Deng, Jiaxin, et autres
Publié: (2024)

Modeling the Popularity of Events on Web by Sparsity and Mutual-Excitation Guided Graph Neural Network
par: Deng, Jiaxin, et autres
Publié: (2024)

Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
par: Shen, Lingzhi, et autres
Publié: (2025)

Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes
par: Li, Aodi, et autres
Publié: (2024)

Adaptively Sampling-Reusing-Mixing Decomposed Gradients to Speed Up Sharpness Aware Minimization
par: Deng, Jiaxin, et autres
Publié: (2025)

MEC-Quant: Maximum Entropy Coding for Extremely Low Bit Quantization-Aware Training
par: Pang, Junbiao, et autres
Publié: (2025)

Phased Instruction Fine-Tuning for Large Language Models
par: Pang, Wei, et autres
Publié: (2024)

Unveiling the Generalization Power of Fine-Tuned Large Language Models
par: Yang, Haoran, et autres
Publié: (2024)

Parameter-Efficient Fine-Tuning With Adapters
par: Chen, Keyu, et autres
Publié: (2024)

Structure-Learnable Adapter Fine-Tuning for Parameter-Efficient Large Language Models
par: Gong, Ming, et autres
Publié: (2025)

In-Distribution Consistency Regularization Improves the Generalization of Quantization-Aware Training
par: Pang, Junbiao, et autres
Publié: (2024)

Unified Defense for Large Language Models against Jailbreak and Fine-Tuning Attacks in Education
par: Yi, Xin, et autres
Publié: (2025)

Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
par: Leong, Hui Yi, et autres
Publié: (2024)

Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models
par: Ghiasvand, Sajjad, et autres
Publié: (2024)

Uncovering Limitations of Large Language Models in Information Seeking from Tables
par: Pang, Chaoxu, et autres
Publié: (2024)

Parameter-Efficient Fine-Tuning of Large Language Models via Deconvolution in Subspace
par: Zhang, Jia-Chen, et autres
Publié: (2025)

Boosting Large Language Models with Mask Fine-Tuning
par: Zhang, Mingyuan, et autres
Publié: (2025)

Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection
par: Lim, Ying Fu, et autres
Publié: (2025)

Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
par: Yang, Zhaorui, et autres
Publié: (2024)

NLSR: Neuron-Level Safety Realignment of Large Language Models Against Harmful Fine-Tuning
par: Yi, Xin, et autres
Publié: (2024)

Gradual Learning: Optimizing Fine-Tuning with Partially Mastered Knowledge in Large Language Models
par: Li, Bozhou, et autres
Publié: (2024)

BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
par: Xu, Ran, et autres
Publié: (2024)

An Empirical Study on Parameter-Efficient Fine-Tuning for MultiModal Large Language Models
par: Zhou, Xiongtao, et autres
Publié: (2024)

Enhancing ML Model Interpretability: Leveraging Fine-Tuned Large Language Models for Better Understanding of AI
par: Bokstaller, Jonas, et autres
Publié: (2025)

Privacy-Preserving Parameter-Efficient Fine-Tuning for Large Language Model Services
par: Li, Yansong, et autres
Publié: (2023)

Parameter-Efficient Fine-Tuning of Large Language Models using Semantic Knowledge Tuning
par: Prottasha, Nusrat Jahan, et autres
Publié: (2024)

Reversing Large Language Models for Efficient Training and Fine-Tuning
par: Gal, Eshed, et autres
Publié: (2025)

A Channel-ensemble Approach: Unbiased and Low-variance Pseudo-labels is Critical for Semi-supervised Classification
par: Wu, Jiaqi, et autres
Publié: (2024)

SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
par: Lu, Xudong, et autres
Publié: (2024)

Crafting Efficient Fine-Tuning Strategies for Large Language Models
par: Oliver, Michael, et autres
Publié: (2024)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
par: Weyssow, Martin, et autres
Publié: (2023)

HFT: Half Fine-Tuning for Large Language Models
par: Hui, Tingfeng, et autres
Publié: (2024)

I Learn Better If You Speak My Language: Understanding the Superior Performance of Fine-Tuning Large Language Models with LLM-Generated Responses
par: Ren, Xuan, et autres
Publié: (2024)

Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models
par: Gupta, Sonam, et autres
Publié: (2025)

TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching
par: Zeng, Runjia, et autres
Publié: (2026)

Dissecting Fine-Tuning Unlearning in Large Language Models
par: Hong, Yihuai, et autres
Publié: (2024)

Exploring Multilingual Probing in Large Language Models: A Cross-Language Analysis
par: Li, Daoyang, et autres
Publié: (2024)

Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions
par: Orlikowski, Matthias, et autres
Publié: (2025)