Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment | Paper Citation Record

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Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 26

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A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer cites this paper.

Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 51

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Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation cites this paper.

Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 112

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MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors cites this paper.

MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model Updating cites this paper.

Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model Updating Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Schema as Parameterized Tools for Universal Information Extraction cites this paper.

Schema as Parameterized Tools for Universal Information Extraction Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification cites this paper.

Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Continual Learning in Vision-Language Models via Aligned Model Merging cites this paper.

Continual Learning in Vision-Language Models via Aligned Model Merging Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models cites this paper.

Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy cites this paper.

Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks cites this paper.

SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Meta-Learning and Synthetic Data for Automated Pretraining and Finetuning cites this paper.

Meta-Learning and Synthetic Data for Automated Pretraining and Finetuning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence cites this paper.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning cites this paper.

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models cites this paper.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation cites this paper.

QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Fine-tuning on simulated data outperforms prompting for agent tone of voice cites this paper.

Fine-tuning on simulated data outperforms prompting for agent tone of voice Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Defending Against Prompt Injection With a Few DefensiveTokens cites this paper.

Defending Against Prompt Injection With a Few DefensiveTokens Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Enhancing RLHF with Human Gaze Modeling cites this paper.

Enhancing RLHF with Human Gaze Modeling Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Implementing Adaptations for Vision AutoRegressive Model cites this paper.

Implementing Adaptations for Vision AutoRegressive Model Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning cites this paper.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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The Impact of Fine-tuning Large Language Models on Automated Program Repair cites this paper.

The Impact of Fine-tuning Large Language Models on Automated Program Repair Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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CIgrate: Automating CI Service Migration with Large Language Models cites this paper.

CIgrate: Automating CI Service Migration with Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments cites this paper.

PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation cites this paper.

Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture cites this paper.

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models cites this paper.

DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks cites this paper.

Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Key and Value Weights Are Probably All You Need: On the Necessity of the Query, Key, Value weight Triplet in Self-Attention Transformers cites this paper.

Key and Value Weights Are Probably All You Need: On the Necessity of the Query, Key, Value weight Triplet in Self-Attention Transformers Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Point of Order: Action-Aware LLM Persona Modeling for Data-Grounded Civic Deliberation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models cites this paper.

PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Reconstructing Item Characteristic Curves using Fine-Tuned Large Language Models cites this paper.

Reconstructing Item Characteristic Curves using Fine-Tuned Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap cites this paper.

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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When pre-training hurts LoRA fine-tuning: a dynamical analysis via single-index models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness cites this paper.

HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Task-Centric Personalized Federated Fine-Tuning of Language Models cites this paper.

Task-Centric Personalized Federated Fine-Tuning of Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates cites this paper.

Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates cites this paper.

Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.

TLoRA: Task-aware Low Rank Adaptation of Large Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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SAMoRA: Semantic-Aware Mixture of LoRA Experts for Task-Adaptive Learning cites this paper.

SAMoRA: Semantic-Aware Mixture of LoRA Experts for Task-Adaptive Learning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study cites this paper.

Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning cites this paper.

World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Soft Specialists: $\alpha$-R\'enyi Ensembles for Uncertainty-Aware LLM Post-Training cites this paper.

Soft Specialists: $\alpha$-R\'enyi Ensembles for Uncertainty-Aware LLM Post-Training Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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FMplex: Model Virtualization for Serving Extensible Foundation Models cites this paper.

FMplex: Model Virtualization for Serving Extensible Foundation Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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Exploring Post-Training Alignment of Small Language Models for Biomedical Data-to-Text Generation: A Case Study of Medication Leaflet cites this paper.

Exploring Post-Training Alignment of Small Language Models for Biomedical Data-to-Text Generation: A Case Study of Medication Leaflet Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

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