Copertina

Look Within or Look Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Yongkang, Xu, Xingle, Nie, Ercong, Wang, Zijing, Feng, Shi, Wang, Daling, Li, Qian, Schütze, Hinrich
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning
di: Liu, Yongkang, et al.
Pubblicazione: (2026)

HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy
di: Liu, Yongkang, et al.
Pubblicazione: (2024)

High-Rank Structured Modulation for Parameter-Efficient Fine-Tuning
di: Liu, Yongkang, et al.
Pubblicazione: (2026)

SMoA: Spectrum Modulation Adapter for Parameter-Efficient Fine-Tuning
di: Liu, Yongkang, et al.
Pubblicazione: (2026)

Why Do More Experts Fail? A Theoretical Analysis of Model Merging
di: Wang, Zijing, et al.
Pubblicazione: (2025)

DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging
di: Wang, Zijing, et al.
Pubblicazione: (2026)

A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation
di: Liu, Yongkang, et al.
Pubblicazione: (2024)

PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMs
di: Wang, Zijing, et al.
Pubblicazione: (2026)

SAD: A Large-Scale Strategic Argumentative Dialogue Dataset
di: Liu, Yongkang, et al.
Pubblicazione: (2026)

Evaluate What You Can't Evaluate: Unassessable Quality for Generated Response
di: Liu, Yongkang, et al.
Pubblicazione: (2023)

ChatZero:Zero-shot Cross-Lingual Dialogue Generation via Pseudo-Target Language
di: Liu, Yongkang, et al.
Pubblicazione: (2024)

Mechanistic Understanding and Mitigation of Language Confusion in English-Centric Large Language Models
di: Nie, Ercong, et al.
Pubblicazione: (2025)

MoLAN: A Unified Modality-Aware Noise Dynamic Editing Framework for Multimodal Sentiment Analysis
di: Xu, Xingle, et al.
Pubblicazione: (2025)

Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
di: Zhang, Qi, et al.
Pubblicazione: (2024)

GNNavi: Navigating the Information Flow in Large Language Models by Graph Neural Network
di: Yuan, Shuzhou, et al.
Pubblicazione: (2024)

BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning
di: Nie, Ercong, et al.
Pubblicazione: (2024)

Lost in Multilinguality: Dissecting Cross-lingual Factual Inconsistency in Transformer Language Models
di: Wang, Mingyang, et al.
Pubblicazione: (2025)

Large Language Models as Neurolinguistic Subjects: Discrepancy between Performance and Competence
di: He, Linyang, et al.
Pubblicazione: (2024)

Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models
di: Yuan, Shuzhou, et al.
Pubblicazione: (2025)

Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Markets
di: Kennedy, Molly, et al.
Pubblicazione: (2025)

Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
di: Gao, Ziqi, et al.
Pubblicazione: (2024)

MEKiT: Multi-source Heterogeneous Knowledge Injection Method via Instruction Tuning for Emotion-Cause Pair Extraction
di: Mu, Shiyi, et al.
Pubblicazione: (2025)

Parameter-Efficient Fine-Tuning via Circular Convolution
di: Chen, Aochuan, et al.
Pubblicazione: (2024)

Decomposed Prompting: Probing Multilingual Linguistic Structure Knowledge in Large Language Models
di: Nie, Ercong, et al.
Pubblicazione: (2024)

ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks
di: Ma, Bolei, et al.
Pubblicazione: (2024)

Tracing Multilingual Factual Knowledge Acquisition in Pretraining
di: Liu, Yihong, et al.
Pubblicazione: (2025)

LLM in the Loop: Creating the ParaDeHate Dataset for Hate Speech Detoxification
di: Yuan, Shuzhou, et al.
Pubblicazione: (2025)

Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
di: Shernazarov, Ulugbek, et al.
Pubblicazione: (2026)

Adaptive Parameter-Efficient Federated Fine-Tuning on Heterogeneous Devices
di: Liu, Jun, et al.
Pubblicazione: (2024)

A Closer Look at Personalized Fine-Tuning in Heterogeneous Federated Learning
di: Chen, Minghui, et al.
Pubblicazione: (2025)

From Parameter Dynamics to Risk Scoring : Quantifying Sample-Level Safety Degradation in LLM Fine-tuning
di: Wang, Xiao, et al.
Pubblicazione: (2026)

Muse: A Multimodal Conversational Recommendation Dataset with Scenario-Grounded User Profiles
di: Wang, Zihan, et al.
Pubblicazione: (2024)

Your Pretrained Model Tells the Difficulty Itself: A Self-Adaptive Curriculum Learning Paradigm for Natural Language Understanding
di: Feng, Qi, et al.
Pubblicazione: (2025)

RevFFN: Memory-Efficient Full-Parameter Fine-Tuning of Mixture-of-Experts LLMs with Reversible Blocks
di: Liu, Ningyuan, et al.
Pubblicazione: (2025)

OFA: A Framework of Initializing Unseen Subword Embeddings for Efficient Large-scale Multilingual Continued Pretraining
di: Liu, Yihong, et al.
Pubblicazione: (2023)

Parameter-Efficient Fine-Tuning for Foundation Models
di: Zhang, Dan, et al.
Pubblicazione: (2025)

Look Beyond the Obvious
di: Megan Venzin
Pubblicazione: (2024)

Look Within, Why LLMs Hallucinate: A Causal Perspective
di: Li, He, et al.
Pubblicazione: (2024)

LongForm: Effective Instruction Tuning with Reverse Instructions
di: Köksal, Abdullatif, et al.
Pubblicazione: (2023)

FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning
di: Zhao, Yequan, et al.
Pubblicazione: (2026)