Cover Image

Selecting Large Language Model to Fine-tune via Rectified Scaling Law

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Haowei, Huang, Baizhou, Ye, Haotian, Chen, Qinyu, Wang, Zihao, Li, Sujian, Ma, Jianzhu, Wan, Xiaojun, Zou, James, Liang, Yitao
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Evaluation of Complex Reasoning in Large Language Models
by: Lin, Haowei, et al.
Published: (2025)

Can Language Models Discover Scaling Laws?
by: Lin, Haowei, et al.
Published: (2025)

Inference-time Scaling of Diffusion Models through Classical Search
by: Zhang, Xiangcheng, et al.
Published: (2025)

TFG-Flow: Training-free Guidance in Multimodal Generative Flow
by: Lin, Haowei, et al.
Published: (2025)

WaterPool: A Watermark Mitigating Trade-offs among Imperceptibility, Efficacy and Robustness
by: Huang, Baizhou, et al.
Published: (2024)

TFG: Unified Training-Free Guidance for Diffusion Models
by: Ye, Haotian, et al.
Published: (2024)

Enhancing LLM Watermark Resilience Against Both Scrubbing and Spoofing Attacks
by: Shen, Huanming, et al.
Published: (2025)

QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs
by: Zhu, Junlin, et al.
Published: (2026)

$B^4$: A Black-Box Scrubbing Attack on LLM Watermarks
by: Huang, Baizhou, et al.
Published: (2024)

Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency
by: Huang, Baizhou, et al.
Published: (2023)

JARVIS-VLA: Post-Training Large-Scale Vision Language Models to Play Visual Games with Keyboards and Mouse
by: Li, Muyao, et al.
Published: (2025)

Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models
by: Ye, Haotian, et al.
Published: (2025)

RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation
by: Wang, Zihao, et al.
Published: (2024)

MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency
by: Zhang, Junzhe, et al.
Published: (2024)

CLoG: Benchmarking Continual Learning of Image Generation Models
by: Zhang, Haotian, et al.
Published: (2024)

Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents
by: Wang, Zihao, et al.
Published: (2023)

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation
by: Wang, Yibo, et al.
Published: (2025)

GROOT-2: Weakly Supervised Multi-Modal Instruction Following Agents
by: Cai, Shaofei, et al.
Published: (2024)

MCU: An Evaluation Framework for Open-Ended Game Agents
by: Zheng, Xinyue, et al.
Published: (2023)

Scaling Laws for State Dynamics in Large Language Models
by: Li, Jacob X, et al.
Published: (2025)

A Neural Symbolic Model for Space Physics
by: Ying, Jie, et al.
Published: (2025)

Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining
by: Xiong, Weimin, et al.
Published: (2026)

Temporal Scaling Law for Large Language Models
by: Xiong, Yizhe, et al.
Published: (2024)

Disentangling Reasoning Tokens and Boilerplate Tokens For Language Model Fine-tuning
by: Ye, Ziang, et al.
Published: (2024)

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

OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents
by: Wang, Zihao, et al.
Published: (2024)

MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosis
by: Zhu, Yitao, et al.
Published: (2023)

Fine-tuning of Large Language Models for Domain-Specific Cybersecurity Knowledge
by: Huang, Yuan
Published: (2025)

BlockPruner: Fine-grained Pruning for Large Language Models
by: Zhong, Longguang, et al.
Published: (2024)

Towards Comprehensible Recommendation with Large Language Model Fine-tuning
by: Luo, Yunze, et al.
Published: (2025)

Fine-tuning Large Language Model for Automated Algorithm Design
by: Liu, Fei, et al.
Published: (2025)

Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection
by: Li, Sijie, et al.
Published: (2026)

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models
by: Ji, Xiaoshuang, et al.
Published: (2025)

Fine-tuning Multimodal Large Language Models for Product Bundling
by: Liu, Xiaohao, et al.
Published: (2024)

Scaling Laws for Forgetting When Fine-Tuning Large Language Models
by: Kalajdzievski, Damjan
Published: (2024)

Automated Retrosynthesis Planning of Macromolecules Using Large Language Models and Knowledge Graphs
by: Ma, Qinyu, et al.
Published: (2025)

Fine-tuning Large Language Models for Domain-specific Machine Translation
by: Zheng, Jiawei, et al.
Published: (2024)

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
by: Huang, Wei, et al.
Published: (2025)

Selective Pre-training for Private Fine-tuning
by: Yu, Da, et al.
Published: (2023)

Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning
by: Huang, Tiansheng, et al.
Published: (2024)