Saved in:
| Main Authors: | Qi, Haomin, Dai, Zihan, Huang, Chengbo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.18076 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Governance-Aware Hybrid Fine-Tuning for Multilingual Large Language Models
by: Qi, Haomin, et al.
Published: (2025)
by: Qi, Haomin, et al.
Published: (2025)
PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models
by: Belanec, Robert, et al.
Published: (2025)
by: Belanec, Robert, et al.
Published: (2025)
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models
by: Prottasha, Nusrat Jahan, et al.
Published: (2025)
by: Prottasha, Nusrat Jahan, et al.
Published: (2025)
TS-PEFT: Unveiling Token-Level Redundancy in Parameter-Efficient Fine-Tuning
by: Ma, Dabiao, et al.
Published: (2025)
by: Ma, Dabiao, et al.
Published: (2025)
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2024)
by: Peng, Zhiyuan, et al.
Published: (2024)
Enhancing Low-Resource LLMs Classification with PEFT and Synthetic Data
by: Patwa, Parth, et al.
Published: (2024)
by: Patwa, Parth, et al.
Published: (2024)
Challenges in Adapting Multilingual LLMs to Low-Resource Languages using LoRA PEFT Tuning
by: Khade, Omkar, et al.
Published: (2024)
by: Khade, Omkar, et al.
Published: (2024)
PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark
by: Belanec, Robert, et al.
Published: (2025)
by: Belanec, Robert, et al.
Published: (2025)
Reliable Control-Point Selection for Steering Reasoning in Large Language Models
by: Zhuang, Haomin, et al.
Published: (2026)
by: Zhuang, Haomin, et al.
Published: (2026)
ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning
by: Li, Xianming, et al.
Published: (2026)
by: Li, Xianming, et al.
Published: (2026)
PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization
by: Clarke, Christopher, et al.
Published: (2024)
by: Clarke, Christopher, et al.
Published: (2024)
Train More Parameters But Mind Their Placement: Insights into Language Adaptation with PEFT
by: Kunz, Jenny
Published: (2024)
by: Kunz, Jenny
Published: (2024)
PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective
by: Huang, Yangyi, et al.
Published: (2026)
by: Huang, Yangyi, et al.
Published: (2026)
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning
by: Gu, Naibin, et al.
Published: (2024)
by: Gu, Naibin, et al.
Published: (2024)
Alignment for Efficient Tool Calling of Large Language Models
by: Xu, Hongshen, et al.
Published: (2025)
by: Xu, Hongshen, et al.
Published: (2025)
Efficient Language Modeling for Low-Resource Settings with Hybrid RNN-Transformer Architectures
by: Lindenmaier, Gabriel, et al.
Published: (2025)
by: Lindenmaier, Gabriel, et al.
Published: (2025)
On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters
by: Lab, Mind, et al.
Published: (2026)
by: Lab, Mind, et al.
Published: (2026)
MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
by: Yoshimura, Masakazu, et al.
Published: (2024)
by: Yoshimura, Masakazu, et al.
Published: (2024)
HD-Eval: Aligning Large Language Model Evaluators Through Hierarchical Criteria Decomposition
by: Liu, Yuxuan, et al.
Published: (2024)
by: Liu, Yuxuan, et al.
Published: (2024)
OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models
by: Wen, Haomin, et al.
Published: (2024)
by: Wen, Haomin, et al.
Published: (2024)
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
by: Zhao, Zekai, et al.
Published: (2025)
by: Zhao, Zekai, et al.
Published: (2025)
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
by: Zhou, Han, et al.
Published: (2023)
by: Zhou, Han, et al.
Published: (2023)
FISH-Tuning: Enhancing PEFT Methods with Fisher Information
by: Xue, Kang, et al.
Published: (2025)
by: Xue, Kang, et al.
Published: (2025)
Towards Resource Efficient and Interpretable Bias Mitigation in Large Language Models
by: Tong, Schrasing, et al.
Published: (2024)
by: Tong, Schrasing, et al.
Published: (2024)
Monkey Jump : MoE-Style PEFT for Efficient Multi-Task Learning
by: Prottasha, Nusrat Jahan, et al.
Published: (2026)
by: Prottasha, Nusrat Jahan, et al.
Published: (2026)
SDSAT: Accelerating LLM Inference through Speculative Decoding with Semantic Adaptive Tokens
by: Liu, Chengbo, et al.
Published: (2024)
by: Liu, Chengbo, et al.
Published: (2024)
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization
by: Yadav, Prateek, et al.
Published: (2023)
by: Yadav, Prateek, et al.
Published: (2023)
Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?
by: Huang, Yue, et al.
Published: (2024)
by: Huang, Yue, et al.
Published: (2024)
How to Tune a Multilingual Encoder Model for Germanic Languages: A Study of PEFT, Full Fine-Tuning, and Language Adapters
by: Oji, Romina, et al.
Published: (2025)
by: Oji, Romina, et al.
Published: (2025)
A Hybrid Framework with Large Language Models for Rare Disease Phenotyping
by: Wu, Jinge, et al.
Published: (2024)
by: Wu, Jinge, et al.
Published: (2024)
Punctuation-aware Hybrid Trainable Sparse Attention for Large Language Models
by: Qiu, Junxiang, et al.
Published: (2026)
by: Qiu, Junxiang, et al.
Published: (2026)
A Closer Look into Mixture-of-Experts in Large Language Models
by: Lo, Ka Man, et al.
Published: (2024)
by: Lo, Ka Man, et al.
Published: (2024)
Efficient Sequential Decision Making with Large Language Models
by: Chen, Dingyang, et al.
Published: (2024)
by: Chen, Dingyang, et al.
Published: (2024)
OutlierTune: Efficient Channel-Wise Quantization for Large Language Models
by: Wang, Jinguang, et al.
Published: (2024)
by: Wang, Jinguang, et al.
Published: (2024)
LMCD: Language Models are Zeroshot Cognitive Diagnosis Learners
by: He, Yu, et al.
Published: (2025)
by: He, Yu, et al.
Published: (2025)
GraphCue for SDN Configuration Code Synthesis
by: Qi, Haomin, et al.
Published: (2025)
by: Qi, Haomin, et al.
Published: (2025)
Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
by: Kaddour, Jean, et al.
Published: (2023)
by: Kaddour, Jean, et al.
Published: (2023)
E5-V: Universal Embeddings with Multimodal Large Language Models
by: Jiang, Ting, et al.
Published: (2024)
by: Jiang, Ting, et al.
Published: (2024)
Resource-Efficient Medical Report Generation using Large Language Models
by: Abdullah, et al.
Published: (2024)
by: Abdullah, et al.
Published: (2024)
Efficient Deployment of Large Language Models on Resource-constrained Devices
by: Yao, Zhiwei, et al.
Published: (2025)
by: Yao, Zhiwei, et al.
Published: (2025)
Similar Items
-
Governance-Aware Hybrid Fine-Tuning for Multilingual Large Language Models
by: Qi, Haomin, et al.
Published: (2025) -
PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models
by: Belanec, Robert, et al.
Published: (2025) -
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models
by: Prottasha, Nusrat Jahan, et al.
Published: (2025) -
TS-PEFT: Unveiling Token-Level Redundancy in Parameter-Efficient Fine-Tuning
by: Ma, Dabiao, et al.
Published: (2025) -
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2024)