Imagen de Portada

BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Shiwei, Luo, Xiandi, Wang, Haozhao, Tang, Xing, Cui, Ziqiang, Liu, Dugang, Li, Yuhua, He, Xiuqiang, Li, Ruixuan
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation
por: Li, Shiwei, et al.
Publicado: (2025)

The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
por: Li, Shiwei, et al.
Publicado: (2025)

Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
por: Li, Shiwei, et al.
Publicado: (2025)

BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation
por: Wang, Qiushi, et al.
Publicado: (2024)

Masked Random Noise for Communication Efficient Federated Learning
por: Li, Shiwei, et al.
Publicado: (2024)

Nonlinearity as Rank: Generative Low-Rank Adapter with Radial Basis Functions
por: Ouyang, Yihao, et al.
Publicado: (2026)

Mixed-Precision Embeddings for Large-Scale Recommendation Models
por: Li, Shiwei, et al.
Publicado: (2024)

BoRA: Bayesian Hierarchical Low-Rank Adaption for Multi-Task Large Language Models
por: Eide, Simen, et al.
Publicado: (2024)

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
por: Li, Shiwei, et al.
Publicado: (2024)

Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation
por: Cui, Ziqiang, et al.
Publicado: (2025)

Retrieve-then-Adapt: Retrieval-Augmented Test-Time Adaptation for Sequential Recommendation
por: Tang, Xing, et al.
Publicado: (2026)

Comprehending Knowledge Graphs with Large Language Models for Recommender Systems
por: Cui, Ziqiang, et al.
Publicado: (2024)

Less Is More: Elevating RAG via Performance-Driven Context Compression
por: Cui, Ziqiang, et al.
Publicado: (2025)

Automated Information Flow Selection for Multi-scenario Multi-task Recommendation
por: Yang, Chaohua, et al.
Publicado: (2025)

Data-Driven Function Calling Improvements in Large Language Model for Online Financial QA
por: Tang, Xing, et al.
Publicado: (2026)

FedMM: Federated Collaborative Signal Quantization for Multi-Market CTR Prediction
por: Zhang, Jun, et al.
Publicado: (2026)

Expected Transaction Value Optimization for Precise Marketing in FinTech Platforms
por: Weng, Yunpeng, et al.
Publicado: (2024)

A Predict-Then-Optimize Customer Allocation Framework for Online Fund Recommendation
por: Tang, Xing, et al.
Publicado: (2025)

Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
por: Tang, Xing, et al.
Publicado: (2024)

TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition
por: Lin, Tianwei, et al.
Publicado: (2024)

End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling
por: Sun, Zexu, et al.
Publicado: (2024)

Optimizing Feature Set for Click-Through Rate Prediction
por: Lyu, Fuyuan, et al.
Publicado: (2023)

FedBiF: Communication-Efficient Federated Learning via Bits Freezing
por: Li, Shiwei, et al.
Publicado: (2025)

GeoRA: Geometry-Aware Low-Rank Adaptation for RLVR
por: Zhang, Jiaying, et al.
Publicado: (2026)

The Expressive Power of Low-Rank Adaptation
por: Zeng, Yuchen, et al.
Publicado: (2023)

LoRA-GA: Low-Rank Adaptation with Gradient Approximation
por: Wang, Shaowen, et al.
Publicado: (2024)

Less is More: Resource-Efficient Low-Rank Adaptation
por: Tian, Chunlin, et al.
Publicado: (2025)

Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
por: Li, Tao, et al.
Publicado: (2024)

Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
por: Yi, Shuai, et al.
Publicado: (2026)

TsqLoRA: Towards Sensitivity and Quality Low-Rank Adaptation for Efficient Fine-Tuning
por: Chen, Yu, et al.
Publicado: (2025)

Null-LoRA: Low-Rank Adaptation on Null Space
por: Zhang, Yi, et al.
Publicado: (2025)

Stable-LoRA: Stabilizing Feature Learning of Low-Rank Adaptation
por: Wu, Yize, et al.
Publicado: (2026)

Benchmarking for Deep Uplift Modeling in Online Marketing
por: Liu, Dugang, et al.
Publicado: (2024)

OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
por: Weng, Yunpeng, et al.
Publicado: (2024)

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
por: Liu, Yuhan, et al.
Publicado: (2025)

Towards Efficient Replay in Federated Incremental Learning
por: Li, Yichen, et al.
Publicado: (2024)

DenseLoRA: Dense Low-Rank Adaptation of Large Language Models
por: Mu, Lin, et al.
Publicado: (2025)

HiLoRA: Hierarchical Low-Rank Adaptation for Personalized Federated Learning
por: Peng, Zihao, et al.
Publicado: (2026)

InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning
por: Liang, Yan-Shuo, et al.
Publicado: (2024)

SBoRA: Low-Rank Adaptation with Regional Weight Updates
por: Po, Lai-Man, et al.
Publicado: (2024)