LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Lanxin, Mishra, Bamdev, Jawanpuria, Pratik, Lin, Lequan, Shi, Dai, Gao, Junbin, Han, Andi |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Riemannian Approach to Ground Metric Learning for Optimal Transport
by: Jawanpuria, Pratik, et al.
Published: (2024)
by: Jawanpuria, Pratik, et al.
Published: (2024)
Riemannian coordinate descent algorithms on matrix manifolds
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
Riemannian Optimization for Hadamard Products of Low-Rank Matrices
by: Jawanpuria, Pratik, et al.
Published: (2026)
by: Jawanpuria, Pratik, et al.
Published: (2026)
Generalized infinite dimensional Alpha-Procrustes based geometries
by: Goomanee, Salvish, et al.
Published: (2025)
by: Goomanee, Salvish, et al.
Published: (2025)
A Framework for Bilevel Optimization on Riemannian Manifolds
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
Nyström Approximation on Manifolds
by: Nie, Hantao, et al.
Published: (2026)
by: Nie, Hantao, et al.
Published: (2026)
Unleash Graph Neural Networks from Heavy Tuning
by: Lin, Lequan, et al.
Published: (2024)
by: Lin, Lequan, et al.
Published: (2024)
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
by: Lin, Lequan, et al.
Published: (2024)
by: Lin, Lequan, et al.
Published: (2024)
Riemannian Federated Learning via Averaging Gradient Streams
by: Huang, Zhenwei, et al.
Published: (2024)
by: Huang, Zhenwei, et al.
Published: (2024)
SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting
by: Lin, Lequan, et al.
Published: (2024)
by: Lin, Lequan, et al.
Published: (2024)
A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks
by: Mishra, Neel, et al.
Published: (2024)
by: Mishra, Neel, et al.
Published: (2024)
Federated Learning on Riemannian Manifolds with Differential Privacy
by: Huang, Zhenwei, et al.
Published: (2024)
by: Huang, Zhenwei, et al.
Published: (2024)
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
UniPROT: Uniform Prototype Selection via Partial Optimal Transport with Submodular Guarantees
by: Chanda, Prateek, et al.
Published: (2026)
by: Chanda, Prateek, et al.
Published: (2026)
Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds
by: Li, Yibang, et al.
Published: (2026)
by: Li, Yibang, et al.
Published: (2026)
When Graph Neural Networks Meet Dynamic Mode Decomposition
by: Shi, Dai, et al.
Published: (2024)
by: Shi, Dai, et al.
Published: (2024)
Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks
by: Shi, Dai, et al.
Published: (2024)
by: Shi, Dai, et al.
Published: (2024)
Submodular Framework for Structured-Sparse Optimal Transport
by: Manupriya, Piyushi, et al.
Published: (2024)
by: Manupriya, Piyushi, et al.
Published: (2024)
Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
by: Shi, Dai, et al.
Published: (2026)
by: Shi, Dai, et al.
Published: (2026)
S$^3$GNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning
by: Shi, Dai, et al.
Published: (2026)
by: Shi, Dai, et al.
Published: (2026)
FAAR: Efficient Frequency-Aware Multi-Task Fine-Tuning via Automatic Rank Selection
by: Fontana, Maxime, et al.
Published: (2026)
by: Fontana, Maxime, et al.
Published: (2026)
ACT as Human: Multimodal Large Language Model Data Annotation with Critical Thinking
by: Lin, Lequan, et al.
Published: (2025)
by: Lin, Lequan, et al.
Published: (2025)
Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
by: Xiang, Haotian, et al.
Published: (2026)
by: Xiang, Haotian, et al.
Published: (2026)
LoKO: Low-Rank Kalman Optimizer for Online Fine-Tuning of Large Models
by: Abdi, Hossein, et al.
Published: (2024)
by: Abdi, Hossein, et al.
Published: (2024)
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
by: Ma, Xinyu, et al.
Published: (2024)
by: Ma, Xinyu, et al.
Published: (2024)
ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
by: Thompson, Luke, et al.
Published: (2025)
by: Thompson, Luke, et al.
Published: (2025)
FedSEA: Achieving Benefit of Parallelization in Federated Online Learning
by: Sahu, Harekrushna, et al.
Published: (2026)
by: Sahu, Harekrushna, et al.
Published: (2026)
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
by: Zhang, Longteng, et al.
Published: (2026)
by: Zhang, Longteng, et al.
Published: (2026)
Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation
by: Bafghi, Reza Akbarian, et al.
Published: (2025)
by: Bafghi, Reza Akbarian, et al.
Published: (2025)
Selection of LLM Fine-Tuning Data based on Orthogonal Rules
by: Li, Xiaomin, et al.
Published: (2024)
by: Li, Xiaomin, et al.
Published: (2024)
On the Price of Privacy for Language Identification and Generation
by: Li, Xiaoyu, et al.
Published: (2026)
by: Li, Xiaoyu, et al.
Published: (2026)
Contrastive Identification and Generation in the Limit
by: Li, Xiaoyu, et al.
Published: (2026)
by: Li, Xiaoyu, et al.
Published: (2026)
Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
by: Han, Xiao, et al.
Published: (2025)
by: Han, Xiao, et al.
Published: (2025)
Memory-Efficient Fine-Tuning via Low-Rank Activation Compression
by: Shi, Jiang-Xin, et al.
Published: (2025)
by: Shi, Jiang-Xin, et al.
Published: (2025)
MMD-Regularized Unbalanced Optimal Transport
by: Manupriya, Piyushi, et al.
Published: (2020)
by: Manupriya, Piyushi, et al.
Published: (2020)
Wiener Chaos Expansion based Neural Operator for Singular Stochastic Partial Differential Equations
by: Shi, Dai, et al.
Published: (2026)
by: Shi, Dai, et al.
Published: (2026)
Evaluation of retrieval-based QA on QUEST-LOFT
by: Scales, Nathan, et al.
Published: (2025)
by: Scales, Nathan, et al.
Published: (2025)
TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning
by: Han, Xiaosong, et al.
Published: (2026)
by: Han, Xiaosong, et al.
Published: (2026)
Logic and the Foundations of Game and Decision Theory (LOFT 7)
Published: (2010)
Published: (2010)
FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering
by: Ping, Siqi, et al.
Published: (2024)
by: Ping, Siqi, et al.
Published: (2024)
Similar Items
-
A Riemannian Approach to Ground Metric Learning for Optimal Transport
by: Jawanpuria, Pratik, et al.
Published: (2024) -
Riemannian coordinate descent algorithms on matrix manifolds
by: Han, Andi, et al.
Published: (2024) -
Riemannian Optimization for Hadamard Products of Low-Rank Matrices
by: Jawanpuria, Pratik, et al.
Published: (2026) -
Generalized infinite dimensional Alpha-Procrustes based geometries
by: Goomanee, Salvish, et al.
Published: (2025) -
A Framework for Bilevel Optimization on Riemannian Manifolds
by: Han, Andi, et al.
Published: (2024)