Cover Image

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dong, Guanting, Yuan, Hongyi, Lu, Keming, Li, Chengpeng, Xue, Mingfeng, Liu, Dayiheng, Wang, Wei, Yuan, Zheng, Zhou, Chang, Zhou, Jingren
Format:	Preprint
Published:	2023
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

Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models
by: Dong, Guanting, et al.
Published: (2024)

MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
by: Li, Chengpeng, et al.
Published: (2023)

DotaMath: Decomposition of Thought with Code Assistance and Self-correction for Mathematical Reasoning
by: Li, Chengpeng, et al.
Published: (2024)

Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment
by: Lu, Keming, et al.
Published: (2024)

Speculative Contrastive Decoding
by: Yuan, Hongyi, et al.
Published: (2023)

Predicting Rewards Alongside Tokens: Non-disruptive Parameter Insertion for Efficient Inference Intervention in Large Language Model
by: Yuan, Chenhan, et al.
Published: (2024)

When Long Helps Short: How Context Length in Supervised Fine-tuning Affects Behavior of Large Language Models
by: Zheng, Yingming, et al.
Published: (2025)

Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
by: Yang, An, et al.
Published: (2024)

Compositional Subspace Representation Fine-tuning for Adaptive Large Language Models
by: Zhou, Andy
Published: (2025)

ProcessBench: Identifying Process Errors in Mathematical Reasoning
by: Zheng, Chujie, et al.
Published: (2024)

The Harder The Better: Maintaining Supervised Fine-tuning Generalization with Less but Harder Data
by: Shang, Zhaoyang, et al.
Published: (2025)

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

RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
by: Luo, Junyu, et al.
Published: (2024)

Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models
by: Li, Yuan, et al.
Published: (2025)

Privacy-preserving Fine-tuning of Large Language Models through Flatness
by: Chen, Tiejin, et al.
Published: (2024)

Teaching Language Models to Reason with Tools
by: Li, Chengpeng, et al.
Published: (2025)

CoVFT: Context-aware Visual Fine-tuning for Multimodal Large Language Models
by: Zhou, Nan, et al.
Published: (2026)

Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning
by: Lu, Yuheng, et al.
Published: (2025)

Self-Steering Optimization: Autonomous Preference Optimization for Large Language Models
by: Xiang, Hao, et al.
Published: (2024)

Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning
by: Ma, Huan, et al.
Published: (2023)

Targeted Efficient Fine-tuning: Optimizing Parameter Updates with Data-Driven Sample Selection
by: Dong, Ming, et al.
Published: (2024)

ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models
by: Luo, Haoran, et al.
Published: (2023)

An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model
by: Tian, Yuxin, et al.
Published: (2024)

Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics Simulations
by: Dong, Zhehao, et al.
Published: (2025)

Supervised Fine-tuning in turn Improves Visual Foundation Models
by: Jiang, Xiaohu, et al.
Published: (2024)

START: Self-taught Reasoner with Tools
by: Li, Chengpeng, et al.
Published: (2025)

OpenNav: Open-World Navigation with Multimodal Large Language Models
by: Yuan, Mingfeng, et al.
Published: (2025)

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
by: Xue, Yuan, et al.
Published: (2026)

Chain of Execution Supervision Promotes General Reasoning in Large Language Models
by: Chen, Nuo, et al.
Published: (2025)

Self-Evolving Critique Abilities in Large Language Models
by: Tang, Zhengyang, et al.
Published: (2025)

Let's Focus on Neuron: Neuron-Level Supervised Fine-tuning for Large Language Model
by: Xu, Haoyun, et al.
Published: (2024)

Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures
by: Chen, Yiming, et al.
Published: (2024)

Don't Take the Premise for Granted: Evaluating the Premise Critique Ability of Large Language Models
by: Li, Jinzhe, et al.
Published: (2025)

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

LLM Critics Help Catch Bugs in Mathematics: Towards a Better Mathematical Verifier with Natural Language Feedback
by: Gao, Bofei, et al.
Published: (2024)

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
by: Zhou, Yiyang, et al.
Published: (2024)

Semi-supervised Fine-tuning for Large Language Models
by: Luo, Junyu, et al.
Published: (2024)

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods
by: Deotale, Rushikesh, et al.
Published: (2026)

PreAct: Prediction Enhances Agent's Planning Ability
by: Fu, Dayuan, et al.
Published: (2024)

A Survey on Federated Fine-tuning of Large Language Models
by: Wu, Yebo, et al.
Published: (2025)