Cover Image

Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Bohao, Wang, Qingyun, Guo, Yue
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Parameter Efficient Fine-tuning via Explained Variance Adaptation
by: Paischer, Fabian, et al.
Published: (2024)

When More is Less: Understanding Chain-of-Thought Length in LLMs
by: Wu, Yuyang, et al.
Published: (2025)

Packing Analysis: Packing Is More Appropriate for Large Models or Datasets in Supervised Fine-tuning
by: Wang, Shuhe, et al.
Published: (2024)

Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
by: Xu, Jing, et al.
Published: (2024)

AMAQ: Adaptive Mixed-bit Activation Quantization for Collaborative Parameter Efficient Fine-tuning
by: Song, Yurun, et al.
Published: (2025)

Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
by: Song, Haobo, et al.
Published: (2024)

The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification
by: Guo, Yiju, et al.
Published: (2026)

Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2024)

Less is More: Improving LLM Alignment via Preference Data Selection
by: Deng, Xun, et al.
Published: (2025)

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

LIMR: Less is More for RL Scaling
by: Li, Xuefeng, et al.
Published: (2025)

Less is More for Improving Automatic Evaluation of Factual Consistency
by: Wang, Tong, et al.
Published: (2024)

Efficient Model Development through Fine-tuning Transfer
by: Lin, Pin-Jie, et al.
Published: (2025)

Exploring Memorization in Fine-tuned Language Models
by: Zeng, Shenglai, et al.
Published: (2023)

DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
by: Shi, Zhengxiang, et al.
Published: (2023)

Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning
by: Liu, Yong, et al.
Published: (2024)

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

Less is More: Extreme Gradient Boost Rank-1 Adaption for Efficient Finetuning of LLMs
by: Zhang, Yifei, et al.
Published: (2024)

Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
by: Lu, Ning, et al.
Published: (2023)

Supernova: Achieving More with Less in Transformer Architectures
by: Tanase, Andrei-Valentin, et al.
Published: (2025)

Efficient End-to-end Language Model Fine-tuning on Graphs
by: Xue, Rui, et al.
Published: (2023)

Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
by: Ma, Xinyu, et al.
Published: (2024)

Input-Time Scaling: Adding Noise and Irrelevance into Less-Is-More Drastically Improves Reasoning Performance and Efficiency
by: Huang, Rapheal, et al.
Published: (2025)

RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
by: Nikdan, Mahdi, et al.
Published: (2024)

Less is More: Denoising Knowledge Graphs For Retrieval Augmented Generation
by: Zheng, Yilun, et al.
Published: (2025)

Less is More: Local Intrinsic Dimensions of Contextual Language Models
by: Ruppik, Benjamin Matthias, et al.
Published: (2025)

Learn More, Forget Less: A Gradient-Aware Data Selection Approach for LLM
by: Liu, Yibai, et al.
Published: (2025)

SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
by: Lingam, Vijay, et al.
Published: (2024)

Explaining Datasets in Words: Statistical Models with Natural Language Parameters
by: Zhong, Ruiqi, et al.
Published: (2024)

Selecting Large Language Model to Fine-tune via Rectified Scaling Law
by: Lin, Haowei, et al.
Published: (2024)

LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning
by: Huang, Wei, et al.
Published: (2026)

Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
by: Wang, Luping, et al.
Published: (2024)

Mechanistic Fine-tuning for In-context Learning
by: Cho, Hakaze, et al.
Published: (2025)

Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation
by: Riaz, Haris, et al.
Published: (2025)

When Less is Enough: Efficient Inference via Collaborative Reasoning
by: Chen, Yilei, et al.
Published: (2026)

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
by: Chen, Yukang, et al.
Published: (2023)

Fine-tuning can Help Detect Pretraining Data from Large Language Models
by: Zhang, Hengxiang, et al.
Published: (2024)

Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
by: Wang, Ruoyu, et al.
Published: (2024)

Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
by: Shen, Lingzhi, et al.
Published: (2025)