{"total":65,"rows":[{"id":"2403.14608","title":"Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey","created":"2024-03-21","cited_by_count":656,"area":null},{"id":"2312.12148","title":"Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment","created":"2023-12-19","cited_by_count":230,"area":null},{"id":"2407.11046","title":"A Survey on LoRA of Large Language Models","created":"2024-07-08","cited_by_count":67,"area":null},{"id":"2501.13787","title":"Parameter-Efficient Fine-Tuning for Foundation Models","created":"2025-01-23","cited_by_count":45,"area":null},{"id":"2307.16867","title":"Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy","created":"2023-07-31","cited_by_count":44,"area":null},{"id":"2403.20320","title":"MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning","created":"2024-03-29","cited_by_count":44,"area":null},{"id":"2305.06061","title":"Visual Tuning","created":"2023-05-10","cited_by_count":34,"area":null},{"id":"2408.08345","title":"5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks","created":"2024-08-15","cited_by_count":34,"area":null},{"id":"2411.01327","title":"Visual Fourier Prompt Tuning","created":"2024-11-02","cited_by_count":30,"area":null},{"id":"2310.03986","title":"Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation","created":"2023-10-06","cited_by_count":29,"area":null},{"id":"2407.09853","title":"Image Compression for Machine and Human Vision with Spatial-Frequency Adaptation","created":"2024-07-13","cited_by_count":26,"area":null},{"id":"2404.13506","title":"Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications","created":"2024-04-21","cited_by_count":25,"area":null},{"id":"2212.12206","title":"Understanding and Improving Transfer Learning of Deep Models via Neural Collapse","created":"2022-12-23","cited_by_count":24,"area":null},{"id":"2401.00788","title":"Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models","created":"2024-01-01","cited_by_count":23,"area":null},{"id":"2402.02242","title":"Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark","created":"2024-02-03","cited_by_count":23,"area":null},{"id":"2403.19243","title":"Efficient Learning With Sine-Activated Low-rank Matrices","created":"2024-03-28","cited_by_count":22,"area":null},{"id":"2311.15010","title":"Adapter is All You Need for Tuning Visual Tasks","created":"2023-11-25","cited_by_count":19,"area":null},{"id":"2412.07746","title":"LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation Models","created":"2024-12-10","cited_by_count":18,"area":null},{"id":"2404.17245","title":"Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting","created":"2024-04-26","cited_by_count":17,"area":null},{"id":"2406.06420","title":"An Improved Empirical Fisher Approximation for Natural Gradient Descent","created":"2024-06-10","cited_by_count":15,"area":null},{"id":"2410.11160","title":"A Unified Framework with Multimodal Fine-tuning for Remote Sensing Semantic Segmentation","created":"2024-10-15","cited_by_count":15,"area":null},{"id":"2302.06354","title":"Less is More: Selective Layer Finetuning with SubTuning","created":"2023-02-13","cited_by_count":14,"area":null},{"id":"2310.01324","title":"ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video","created":"2023-10-02","cited_by_count":14,"area":null},{"id":"2403.10519","title":"Frozen Feature Augmentation for Few-Shot Image Classification","created":"2024-03-15","cited_by_count":13,"area":null},{"id":"2406.03051","title":"Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision","created":"2024-06-05","cited_by_count":13,"area":null},{"id":"2503.17650","title":"Visual Variational Autoencoder Prompt Tuning","created":"2025-03-22","cited_by_count":10,"area":null},{"id":"2310.13225","title":"Scalable Neural Network Kernels","created":"2023-10-20","cited_by_count":9,"area":null},{"id":"2311.03747","title":"SBCFormer: Lightweight Network Capable of Full-size ImageNet Classification at 1 FPS on Single Board Computers","created":"2023-11-07","cited_by_count":9,"area":null},{"id":"2401.14194","title":"Parameter-Efficient Conversational Recommender System as a Language Processing Task","created":"2024-01-25","cited_by_count":9,"area":null},{"id":"2307.05468","title":"My3DGen: A Scalable Personalized 3D Generative Model","created":"2023-07-11","cited_by_count":8,"area":null},{"id":"2402.04009","title":"Low-rank Attention Side-Tuning for Parameter-Efficient Fine-Tuning","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2403.07576","title":"Fine-grained Prompt Tuning: A Parameter and Memory Efficient Transfer Learning Method for High-resolution Medical Image Classification","created":"2024-03-12","cited_by_count":7,"area":null},{"id":"2312.02923","title":"MoSA: Mixture of Sparse Adapters for Visual Efficient Tuning","created":"2023-12-05","cited_by_count":6,"area":null},{"id":"2406.17740","title":"Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning","created":"2024-06-25","cited_by_count":5,"area":null},{"id":"2407.06504","title":"Reprogramming Distillation for Medical Foundation Models","created":"2024-07-09","cited_by_count":5,"area":null},{"id":"2412.03587","title":"Not All Adapters Matter: Selective Adapter Freezing for Memory-Efficient Fine-Tuning of Language Models","created":"2024-11-26","cited_by_count":5,"area":null},{"id":"2407.11573","title":"Probing the Efficacy of Federated Parameter-Efficient Fine-Tuning of Vision Transformers for Medical Image Classification","created":"2024-07-16","cited_by_count":4,"area":null},{"id":"2409.02838","title":"iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation","created":"2024-09-04","cited_by_count":3,"area":null},{"id":"2503.14836","title":"On the Robustness Tradeoff in Fine-Tuning","created":"2025-03-19","cited_by_count":3,"area":null},{"id":"2403.05930","title":"Deep learning for multi-label classification of coral conditions in the Indo-Pacific via underwater photogrammetry","created":"2024-03-09","cited_by_count":2,"area":null},{"id":"2403.10127","title":"TransLandSeg: A Transfer Learning Approach for Landslide Semantic Segmentation Based on Vision Foundation Model","created":"2024-03-15","cited_by_count":2,"area":null},{"id":"2404.00351","title":"Rethinking Attention-Based Multiple Instance Learning for Whole-Slide Pathological Image Classification: An Instance Attribute Viewpoint","created":"2024-03-30","cited_by_count":2,"area":null},{"id":"2408.02426","title":"Boosting Memory Efficiency in Transfer Learning for High-Resolution Medical Image Classification","created":"2024-08-05","cited_by_count":2,"area":null},{"id":"2410.13841","title":"A Unified View of Delta Parameter Editing in Post-Trained Large-Scale Models","created":"2024-10-17","cited_by_count":2,"area":null},{"id":"2410.17661","title":"PETAH: Parameter Efficient Task Adaptation for Hybrid Transformers in a resource-limited Context","created":"2024-10-23","cited_by_count":2,"area":null},{"id":"2410.21705","title":"AdaptGCD: Multi-Expert Adapter Tuning for Generalized Category Discovery","created":"2024-10-29","cited_by_count":2,"area":null},{"id":"2504.21544","title":"SAM4EM: Efficient memory-based two stage prompt-free segment anything model adapter for complex 3D neuroscience electron microscopy stacks","created":"2025-04-30","cited_by_count":2,"area":null},{"id":"2310.06124","title":"Parameter-efficient Multi-Task and Multi-Domain Learning using Factorized Tensor Networks","created":"2023-10-09","cited_by_count":1,"area":null},{"id":"2403.20080","title":"Mixed-precision Supernet Training from Vision Foundation Models using Low Rank Adapter","created":"2024-03-29","cited_by_count":1,"area":null},{"id":"2604.09088","title":"Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation","created":"2026-04-10","cited_by_count":1,"area":null},{"id":"2401.02424","title":"Mapping of Land Use and Land Cover (LULC) using EuroSAT and Transfer Learning","created":"2023-11-06","cited_by_count":0,"area":null},{"id":"2409.00884","title":"A Novel Hybrid Parameter-Efficient Fine-Tuning Approach for Hippocampus Segmentation and Alzheimer's Disease Diagnosis","created":"2024-09-02","cited_by_count":0,"area":null},{"id":"2410.14713","title":"QuAILoRA: Quantization-Aware Initialization for LoRA","created":"2024-10-09","cited_by_count":0,"area":null},{"id":"2502.06220","title":"FunduSAM: A Specialized Deep Learning Model for Enhanced Optic Disc and Cup Segmentation in Fundus Images","created":"2025-02-10","cited_by_count":0,"area":null},{"id":"2502.13568","title":"LSR-Adapt: Ultra-Efficient Parameter Tuning with Matrix Low Separation Rank Kernel Adaptation","created":"2025-02-19","cited_by_count":0,"area":null},{"id":"2507.08736","title":"Catastrophic Forgetting Mitigation Through Plateau Phase Activity Profiling","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2511.12400","title":"MSLoRA: Multi-Scale Low-Rank Adaptation via Attention Reweighting","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2604.27487","title":"Low Rank Adaptation for Adversarial Perturbation","created":"2026-04-30","cited_by_count":0,"area":null},{"id":"2605.04447","title":"Deep Reprogramming Distillation for Medical Foundation Models","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2606.10196","title":"Fisher-Guided Progressive Parameter Selection for Adaptive Fine-Tuning","created":"2026-06-08","cited_by_count":0,"area":null},{"id":"2606.22383","title":"Structured Hyperedge Adaptation for Parameter-Efficient Fine-Tuning of Vision Transformers","created":"2026-06-21","cited_by_count":0,"area":null},{"id":"2608.07051","title":"YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2608.24469","title":"Low-Rank Ternary Adaptation for Fine-Tuning Transformers","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2609.02282","title":"RouteGraph-Mona: Confusion-Aware Routing Fine-Tuning for Mineral Image Classification","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.33424","title":"A Light Bilevel Refinement Aligns Self-Supervised Representations for Stronger Task-Specific Learning","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}