:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Tao, Jiang, Weisen, Liu, Fanghui, Huang, Xiaolin, Kwok, James T.
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2407.03641
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Effective Structured Prompting by Meta-Learning and Representative Verbalizer
por: Jiang, Weisen, et al.
Publicado: (2023)

RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models
por: Chen, Shuhao, et al.
Publicado: (2024)

End-to-end Kernel Learning via Generative Random Fourier Features
por: Fang, Kun, et al.
Publicado: (2020)

Forward-Backward Reasoning in Large Language Models for Mathematical Verification
por: Jiang, Weisen, et al.
Publicado: (2023)

BYOM: Building Your Own Multi-Task Model For Free
por: Jiang, Weisen, et al.
Publicado: (2023)

RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation
por: Chen, Shuhao, et al.
Publicado: (2026)

Dual-Balancing for Multi-Task Learning
por: Lin, Baijiong, et al.
Publicado: (2023)

Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
por: Chen, Minghui, et al.
Publicado: (2024)

Self-Soupervision: Cooking Model Soups without Labels
por: Fuller, Anthony, et al.
Publicado: (2026)

Enhancing Sharpness-Aware Minimization by Learning Perturbation Radius
por: Wang, Xuehao, et al.
Publicado: (2024)

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection
por: Chen, Shuhao, et al.
Publicado: (2026)

Efficient Pareto Manifold Learning with Low-Rank Structure
por: Chen, Weiyu, et al.
Publicado: (2024)

LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
por: Zhang, Yuanhe, et al.
Publicado: (2025)

Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models
por: Liu, Yuhang, et al.
Publicado: (2025)

SubTrack++ : Gradient Subspace Tracking for Scalable LLM Training
por: Rajabi, Sahar, et al.
Publicado: (2025)

OASIS: Online Activation Subspace Learning for Memory-Efficient Training
por: Choudhary, Sakshi, et al.
Publicado: (2026)

Randomized Gradient Subspaces for Efficient Large Language Model Training
por: Rajabi, Sahar, et al.
Publicado: (2025)

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks
por: Liu, Fanghui, et al.
Publicado: (2024)

LT-Soups: Bridging Head and Tail Classes via Subsampled Model Soups
por: Aminbeidokhti, Masih, et al.
Publicado: (2025)

MetaDefense: Defending Finetuning-based Jailbreak Attack Before and During Generation
por: Jiang, Weisen, et al.
Publicado: (2025)

Self-Regularized Learning Methods
por: Schölpple, Max, et al.
Publicado: (2026)

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models
por: Chen, Yiming, et al.
Publicado: (2025)

A Novel Spatiotemporal Coupling Graph Convolutional Network
por: Bi, Fanghui
Publicado: (2024)

Memory-Efficient LLM Training with Online Subspace Descent
por: Liang, Kaizhao, et al.
Publicado: (2024)

Trainable Weight Averaging: Accelerating Training and Improving Generalization
por: Li, Tao, et al.
Publicado: (2022)

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models
por: Cheng, Hailing, et al.
Publicado: (2026)

Bone Soups: A Seek-and-Soup Model Merging Approach for Controllable Multi-Objective Generation
por: Xie, Guofu, et al.
Publicado: (2025)

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data
por: Zhu, Shuchen, et al.
Publicado: (2026)

Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
por: Zheng, Rui, et al.
Publicado: (2024)

RADIN: Souping on a Budget
por: Menes, Thibaut, et al.
Publicado: (2024)

SALSA: Soup-based Alignment Learning for Stronger Adaptation in RLHF
por: Chegini, Atoosa, et al.
Publicado: (2024)

Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning
por: Yang, Hansi, et al.
Publicado: (2024)

A Survey on Time-Series Pre-Trained Models
por: Ma, Qianli, et al.
Publicado: (2023)

PRAC: Principal-Random Subspace for LLM Activation Compression and Memory-Efficient Training
por: Li, Yanyi, et al.
Publicado: (2026)

Enhanced Soups for Graph Neural Networks
por: Zuber, Joseph, et al.
Publicado: (2025)

Spectral Souping: A Unified Framework for Online Preference Alignment
por: Chow, Yinlam, et al.
Publicado: (2026)

State Soup: In-Context Skill Learning, Retrieval and Mixing
por: Pióro, Maciej, et al.
Publicado: (2024)

Efficient Resource-Constrained Training of Transformers via Subspace Optimization
por: Nguyen, Le-Trung, et al.
Publicado: (2025)

Improving Robustness of Foundation Models in Domain Adaptation with Soup-Adapters
por: Roschkowski, Marco
Publicado: (2025)

Online Continual Learning via Logit Adjusted Softmax
por: Huang, Zhehao, et al.
Publicado: (2023)