SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 935 papers

TitleStatusHype
Is Multiple Object Tracking a Matter of Specialization?—0
Is your LLM trapped in a Mental Set? Investigative study on how mental sets affect the reasoning capabilities of LLMs—0
Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models—0
A Fine-tuning Enhanced RAG System with Quantized Influence Measure as AI Judge—0
High-Accuracy ECG Image Interpretation using Parameter-Efficient LoRA Fine-Tuning with Multimodal LLaMA 3.2—0
DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning—0
HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models—0
HiFi: High-Information Attention Heads Hold for Parameter-Efficient Model Adaptation—0
AuroRA: Breaking Low-Rank Bottleneck of LoRA with Nonlinear Mapping—0
KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning—0
HeLM: Highlighted Evidence augmented Language Model for Enhanced Table-to-Text Generation—0
Know Where You're Going: Meta-Learning for Parameter-Efficient Fine-Tuning—0
Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning—0
L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models—0
HELENE: Hessian Layer-wise Clipping and Gradient Annealing for Accelerating Fine-tuning LLM with Zeroth-order Optimization—0
HD-PiSSA: High-Rank Distributed Orthogonal Adaptation—0
LayerNorm: A key component in parameter-efficient fine-tuning—0
BiLoRA: Almost-Orthogonal Parameter Spaces for Continual Learning—0
EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters—0
A Text-Based Knowledge-Embedded Soft Sensing Modeling Approach for General Industrial Process Tasks Based on Large Language Model—0
Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment—0
Efficiency at Scale: Investigating the Performance of Diminutive Language Models in Clinical Tasks—0
LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning—0
LoRTA: Low Rank Tensor Adaptation of Large Language Models—0
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models—0
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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