LIFT+: Lightweight Fine-Tuning for Long-Tail Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Shi, Jiang-Xin, Wei, Tong, Li, Yu-Feng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
by: Shi, Jiang-Xin, et al.
Published: (2023)
by: Shi, Jiang-Xin, et al.
Published: (2023)
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
by: Shi, Jiang-Xin, et al.
Published: (2024)
by: Shi, Jiang-Xin, et al.
Published: (2024)
Learning from Reduced Labels for Long-Tailed Data
by: Wei, Meng, et al.
Published: (2024)
by: Wei, Meng, et al.
Published: (2024)
Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
by: Feng, Shuai, et al.
Published: (2025)
by: Feng, Shuai, et al.
Published: (2025)
CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model
by: Hou, Shihao, et al.
Published: (2025)
by: Hou, Shihao, et al.
Published: (2025)
Unleashing the Power of Vision-Language Models for Long-Tailed Multi-Label Visual Recognition
by: Tang, Wei, et al.
Published: (2025)
by: Tang, Wei, et al.
Published: (2025)
LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encoding
by: Kazerouni, Amirhossein, et al.
Published: (2025)
by: Kazerouni, Amirhossein, et al.
Published: (2025)
BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learning
by: Zheng, Hongwei, et al.
Published: (2024)
by: Zheng, Hongwei, et al.
Published: (2024)
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
by: Zhou, Zhi, et al.
Published: (2024)
by: Zhou, Zhi, et al.
Published: (2024)
Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
by: Qi, Zhi-Hong, et al.
Published: (2024)
by: Qi, Zhi-Hong, et al.
Published: (2024)
Long-Tail Learning with Rebalanced Contrastive Loss
by: De Alvis, Charika, et al.
Published: (2023)
by: De Alvis, Charika, et al.
Published: (2023)
Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
by: Duan, Chen-Long, et al.
Published: (2024)
by: Duan, Chen-Long, et al.
Published: (2024)
Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation
by: Zhang, Lilin, et al.
Published: (2026)
by: Zhang, Lilin, et al.
Published: (2026)
DELTA: Decoupling Long-Tailed Online Continual Learning
by: Raghavan, Siddeshwar, et al.
Published: (2024)
by: Raghavan, Siddeshwar, et al.
Published: (2024)
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
by: Du, Chaoqun, et al.
Published: (2024)
by: Du, Chaoqun, et al.
Published: (2024)
On The Relationship Between Continual Learning and Long-Tailed Recognition
by: Molahasani, Mahdiyar, et al.
Published: (2023)
by: Molahasani, Mahdiyar, et al.
Published: (2023)
Contrast-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment
by: Lv, Song-Lin, et al.
Published: (2025)
by: Lv, Song-Lin, et al.
Published: (2025)
Vision-Language Models are Strong Noisy Label Detectors
by: Wei, Tong, et al.
Published: (2024)
by: Wei, Tong, et al.
Published: (2024)
Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning
by: Lou, Meng, et al.
Published: (2026)
by: Lou, Meng, et al.
Published: (2026)
Efficient Long-Tail Learning in Latent Space by sampling Synthetic Data
by: Sharma, Nakul
Published: (2025)
by: Sharma, Nakul
Published: (2025)
Robust and Generalizable GNN Fine-Tuning via Uncertainty-aware Adapter Learning
by: Jiang, Bo, et al.
Published: (2025)
by: Jiang, Bo, et al.
Published: (2025)
CGL: Advancing Continual GUI Learning via Reinforcement Fine-Tuning
by: Yao, Zhenquan, et al.
Published: (2026)
by: Yao, Zhenquan, et al.
Published: (2026)
TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection
by: Jung, Yoon Gyo, et al.
Published: (2025)
by: Jung, Yoon Gyo, et al.
Published: (2025)
LoFT: Parameter-Efficient Fine-Tuning for Long-tailed Semi-Supervised Learning in Open-World Scenarios
by: Huang, Zhiyuan, et al.
Published: (2025)
by: Huang, Zhiyuan, et al.
Published: (2025)
On the Robustness Tradeoff in Fine-Tuning
by: Li, Kunyang, et al.
Published: (2025)
by: Li, Kunyang, et al.
Published: (2025)
Learning from Imperfect Text Guidance: Robust Long-Tail Visual Recognition with High-Noise Label
by: Li, Mengke, et al.
Published: (2026)
by: Li, Mengke, et al.
Published: (2026)
AutoFT: Learning an Objective for Robust Fine-Tuning
by: Choi, Caroline, et al.
Published: (2024)
by: Choi, Caroline, et al.
Published: (2024)
GD-FPS: Growth-Driven Feedforward Parameter Selection for Efficient Fine-Tuning
by: Yang, Kenneth, et al.
Published: (2025)
by: Yang, Kenneth, et al.
Published: (2025)
Fine-Tuning is Fine, if Calibrated
by: Mai, Zheda, et al.
Published: (2024)
by: Mai, Zheda, et al.
Published: (2024)
Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning
by: Wang, Yuhua, et al.
Published: (2026)
by: Wang, Yuhua, et al.
Published: (2026)
Conformal Prediction for Long-Tailed Classification
by: Ding, Tiffany, et al.
Published: (2025)
by: Ding, Tiffany, et al.
Published: (2025)
Preserving Domain Generalization in Fine-Tuning via Joint Parameter Selection
by: Pan, Bin, et al.
Published: (2025)
by: Pan, Bin, et al.
Published: (2025)
GRPO-RM: Fine-Tuning Representation Models via GRPO-Driven Reinforcement Learning
by: Xu, Yanchen, et al.
Published: (2025)
by: Xu, Yanchen, et al.
Published: (2025)
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
by: Ren, Li, et al.
Published: (2024)
by: Ren, Li, et al.
Published: (2024)
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune
by: Luo, Mengen, et al.
Published: (2024)
by: Luo, Mengen, et al.
Published: (2024)
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex
by: Mulrooney, Alex, et al.
Published: (2024)
by: Mulrooney, Alex, et al.
Published: (2024)
Task-Specific Directions: Definition, Exploration, and Utilization in Parameter Efficient Fine-Tuning
by: Si, Chongjie, et al.
Published: (2024)
by: Si, Chongjie, et al.
Published: (2024)
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
by: Du, Chaoqun, et al.
Published: (2024)
by: Du, Chaoqun, et al.
Published: (2024)
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
by: Shirkavand, Reza, et al.
Published: (2024)
by: Shirkavand, Reza, et al.
Published: (2024)
Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distribution
by: Özdemir, Zeynep, et al.
Published: (2024)
by: Özdemir, Zeynep, et al.
Published: (2024)
Similar Items
-
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
by: Shi, Jiang-Xin, et al.
Published: (2023) -
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
by: Shi, Jiang-Xin, et al.
Published: (2024) -
Learning from Reduced Labels for Long-Tailed Data
by: Wei, Meng, et al.
Published: (2024) -
Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
by: Feng, Shuai, et al.
Published: (2025) -
CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model
by: Hou, Shihao, et al.
Published: (2025)