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parameter-efficient fine-tuning

Parameter-Efficient Fine-Tuning (PEFT) is a technique used to adapt pre-trained models to new tasks with minimal changes to the model's parameters. This approach is particularly useful in scenarios where computational resources are limited or when it is desirable to maintain the original model's performance on the initial task.

Papers

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Showing 351–400 of 935 papers

TitleStatusHype
Parameter-Efficient Cross-lingual Transfer of Vision and Language Models via Translation-based AlignmentCode0
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma DatasetCode0
Gradient Weight-normalized Low-rank Projection for Efficient LLM TrainingCode0
Gradient Inversion Attacks on Parameter-Efficient Fine-TuningCode0
15,500 Seconds: Lean UAV Classification Leveraging PEFT and Pre-Trained NetworksCode0
NLoRA: Nyström-Initiated Low-Rank Adaptation for Large Language ModelsCode0
On-Device LLM for Context-Aware Wi-Fi RoamingCode0
Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium OrchidsCode0
GNNavi: Navigating the Information Flow in Large Language Models by Graph Neural NetworkCode0
DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned ModelsCode0
GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMsCode0
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuningCode0
Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in MammographyCode0
ASteISR: Adapting Single Image Super-resolution Pre-trained Model for Efficient Stereo Image Super-resolutionCode0
CustomTTT: Motion and Appearance Customized Video Generation via Test-Time TrainingCode0
PatchProt: Hydrophobic patch prediction using protein foundation modelsCode0
Music for All: Representational Bias and Cross-Cultural Adaptability of Music Generation ModelsCode0
MU-Bench: A Multitask Multimodal Benchmark for Machine UnlearningCode0
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering TasksCode0
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete DiffusionCode0
MSPLoRA: A Multi-Scale Pyramid Low-Rank Adaptation for Efficient Model Fine-TuningCode0
Navigating the Landscape of Large Language Models: A Comprehensive Review and Analysis of Paradigms and Fine-Tuning StrategiesCode0
QEFT: Quantization for Efficient Fine-Tuning of LLMsCode0
Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised ModelsCode0
Addressing Overprescribing Challenges: Fine-Tuning Large Language Models for Medication Recommendation TasksCode0
CROSSAN: Towards Efficient and Effective Adaptation of Multiple Multimodal Foundation Models for Sequential RecommendationCode0
DLP: Dynamic Layerwise Pruning in Large Language ModelsCode0
Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language ModelsCode0
From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in TransformersCode0
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRACode0
MoLEx: Mixture of Layer Experts for Finetuning with Sparse UpcyclingCode0
FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated LearningCode0
AdCare-VLM: Leveraging Large Vision Language Model (LVLM) to Monitor Long-Term Medication Adherence and CareCode0
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-LearningCode0
Memba: Membrane-driven Parameter-Efficient Fine-Tuning for MambaCode0
MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter SelectionCode0
Domain-Inspired Sharpness-Aware Minimization Under Domain ShiftsCode0
RCA: Region Conditioned Adaptation for Visual Abductive ReasoningCode0
Conversational Factor Information Retrieval Model (ConFIRM)Code0
AR-RAG: Autoregressive Retrieval Augmentation for Image GenerationCode0
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy InterpolationCode0
AROMA: Autonomous Rank-one Matrix AdaptationCode0
Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content?Code0
Low-Rank Adaption on Transformer-based Oriented Object Detector for Satellite Onboard Processing of Remote Sensing ImagesCode0
Interweaving Memories of a Siamese Large Language ModelCode0
LoSiA: Efficient High-Rank Fine-Tuning via Subnet Localization and OptimizationCode0
LoRA Training in the NTK Regime has No Spurious Local MinimaCode0
Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classificationCode0
Low-Rank Interconnected Adaptation across LayersCode0
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task LearningCode0
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All datasetsBoolQHellaSwagWinoGrande

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LLaMA2-7bAccuracy (% )82.63—Unverified
2LLaMA2-7bAccuracy (% )82.63—Unverified
3LLaMA2-7bAccuracy (% )81.93—Unverified
4LLaMA2-7bAccuracy (% )80.28—Unverified
#ModelMetricClaimedVerifiedStatus
1LLaMA2-7bAccuracy (% )76.68—Unverified
2LLaMA2-7bAccuracy (% )76.67—Unverified
3LLaMA2-7bAccuracy (% )76.27—Unverified
#ModelMetricClaimedVerifiedStatus
1LLaMA2-7bAccuracy (% )70.8—Unverified
2LLaMA2-7bAccuracy (% )70.09—Unverified
3LLaMA2-7bAccuracy (% )69.85—Unverified