Cover Image

SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shen, Han, Chen, Pin-Yu, Das, Payel, Chen, Tianyi
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

Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models
by: Chen, Pin-Yu, et al.
Published: (2025)

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
by: Lee, Yu-Ang, et al.
Published: (2026)

Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
by: Sun, Yifan, et al.
Published: (2025)

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning
by: Perin, Gabriel J., et al.
Published: (2025)

Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning
by: Li, Ming, et al.
Published: (2024)

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

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

Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates
by: Lyu, Kaifeng, et al.
Published: (2024)

GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning
by: Yang, Ningyuan, et al.
Published: (2026)

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

Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
by: Zou, Heming, et al.
Published: (2025)

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

Filter-then-Weight: Online Data Selection and Reweighting for LLM Fine-Tuning
by: Wang, Fangxin, et al.
Published: (2026)

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

Outlier-weighed Layerwise Sampling for LLM Fine-tuning
by: Li, Pengxiang, et al.
Published: (2024)

Generation Constraint Scaling Can Mitigate Hallucination
by: Kollias, Georgios, et al.
Published: (2024)

Multitask Mayhem: Unveiling and Mitigating Safety Gaps in LLMs Fine-tuning
by: Jan, Essa, et al.
Published: (2024)

Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning
by: Qian, Livia, et al.
Published: (2026)

Large Language Models can be Strong Self-Detoxifiers
by: Ko, Ching-Yun, et al.
Published: (2024)

Selection of LLM Fine-Tuning Data based on Orthogonal Rules
by: Li, Xiaomin, et al.
Published: (2024)

RuleR: Improving LLM Controllability by Rule-based Data Recycling
by: Li, Ming, et al.
Published: (2024)

SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
by: Yang, Yu, et al.
Published: (2024)

Understanding Forgetting in LLM Supervised Fine-Tuning and Preference Learning -- A Convex Optimization Perspective
by: Fernando, Heshan, et al.
Published: (2024)

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation
by: Marín, Javier
Published: (2025)

SEAL: Systematic Error Analysis for Value ALignment
by: Revel, Manon, et al.
Published: (2024)

Transformer Copilot: Learning from The Mistake Log in LLM Fine-tuning
by: Zou, Jiaru, et al.
Published: (2025)

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

Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection
by: Niu, Tianyi, et al.
Published: (2026)

SEAL: Scaling to Emphasize Attention for Long-Context Retrieval
by: Lee, Changhun, et al.
Published: (2025)

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

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

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization
by: Wang, Dongwei, et al.
Published: (2024)

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

Align Once, Benefit Multilingually: Enforcing Multilingual Consistency for LLM Safety Alignment
by: Bu, Yuyan, et al.
Published: (2026)

Mitigating Training Imbalance in LLM Fine-Tuning via Selective Parameter Merging
by: Ju, Yiming, 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)

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing
by: Tran, Thien Q., et al.
Published: (2025)

Aligning Large Language Models via Fine-grained Supervision
by: Xu, Dehong, et al.
Published: (2024)

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

Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
by: Tan, Qitao, et al.
Published: (2025)