Image de couverture de livre

TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Jipeng, Qin, Yaxuan, Pi, Renjie, Zhang, Weizhong, Pan, Rui, Zhang, Tong
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
par: Pan, Rui, et autres
Publié: (2024)

Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training
par: Pan, Rui, et autres
Publié: (2025)

ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
par: Wu, Yang, et autres
Publié: (2024)

Uncertainty-Aware Gradient Signal-to-Noise Data Selection for Instruction Tuning
par: Yuan, Zhihang, et autres
Publié: (2026)

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs
par: Wang, Zige, et autres
Publié: (2025)

Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning
par: Li, Ming, et autres
Publié: (2024)

The Best Instruction-Tuning Data are Those That Fit
par: Zhang, Dylan, et autres
Publié: (2025)

Instruction Mining: Instruction Data Selection for Tuning Large Language Models
par: Cao, Yihan, et autres
Publié: (2023)

LESS: Selecting Influential Data for Targeted Instruction Tuning
par: Xia, Mengzhou, et autres
Publié: (2024)

Speculative Coreset Selection for Task-Specific Fine-tuning
par: Zhang, Xiaoyu, et autres
Publié: (2024)

SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection
par: Liu, Liangxin, et autres
Publié: (2024)

UPCORE: Utility-Preserving Coreset Selection for Balanced Unlearning
par: Patil, Vaidehi, et autres
Publié: (2025)

Federated Data-Efficient Instruction Tuning for Large Language Models
par: Qin, Zhen, et autres
Publié: (2024)

Plum: Prompt Learning using Metaheuristic
par: Pan, Rui, et autres
Publié: (2023)

TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts
par: Wang, Ruida, et autres
Publié: (2024)

GradientSpace: Unsupervised Data Clustering for Improved Instruction Tuning
par: Sridharan, Shrihari, et autres
Publié: (2025)

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities
par: Dai, Qirun, et autres
Publié: (2025)

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
par: Liu, Wei, et autres
Publié: (2023)

Instruction Tuning for Large Language Models: A Survey
par: Zhang, Shengyu, et autres
Publié: (2023)

Selection of LLM Fine-Tuning Data based on Orthogonal Rules
par: Li, Xiaomin, et autres
Publié: (2024)

Instruction Diversity Drives Generalization To Unseen Tasks
par: Zhang, Dylan, et autres
Publié: (2024)

MathScale: Scaling Instruction Tuning for Mathematical Reasoning
par: Tang, Zhengyang, et autres
Publié: (2024)

Instruction-Tuned, but Not More Verifiable Instruction-Following: A Cross-Task Diagnosis for LoRA Adapters
par: Zou, Junyi
Publié: (2026)

Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
par: Nguyen, Dang, et autres
Publié: (2024)

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation
par: Zhang, Ziniu, et autres
Publié: (2025)

Picky LLMs and Unreliable RMs: An Empirical Study on Safety Alignment after Instruction Tuning
par: Li, Guanlin, et autres
Publié: (2025)

SMART: Submodular Data Mixture Strategy for Instruction Tuning
par: Renduchintala, H S V N S Kowndinya, et autres
Publié: (2024)

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe
par: Xiao, Yuxin, et autres
Publié: (2024)

MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving
par: Wang, Ruida, et autres
Publié: (2025)

Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing
par: Zhang, Yi-Kai, et autres
Publié: (2025)

Fox-1: Open Small Language Model for Cloud and Edge
par: Hu, Zijian, et autres
Publié: (2024)

From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning
par: Wu, Xuansheng, et autres
Publié: (2023)

Contrastive Instruction Tuning
par: Yan, Tianyi Lorena, et autres
Publié: (2024)

Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder
par: Yang, Xianjun, et autres
Publié: (2025)

Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs
par: Kang, Feiyang, et autres
Publié: (2024)

Class-Proportional Coreset Selection for Difficulty-Separable Data
par: Tsai, Elisa, et autres
Publié: (2025)

Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Merging
par: Hui, Tingfeng, et autres
Publié: (2024)

Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks
par: Zhang, Xiaomei, et autres
Publié: (2025)

LongForm: Effective Instruction Tuning with Reverse Instructions
par: Köksal, Abdullatif, et autres
Publié: (2023)

Selective Prompting Tuning for Personalized Conversations with LLMs
par: Huang, Qiushi, et autres
Publié: (2024)