Saved in:
| Main Authors: | Zhang, Zhexin, Sun, Yuhao, Yang, Junxiao, Cui, Shiyao, Zhang, Yuanchao, Wang, Hongning, Huang, Minlie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.15656 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
When Smiley Turns Hostile: Interpreting How Emojis Trigger LLMs' Toxicity
by: Cui, Shiyao, et al.
Published: (2025)
by: Cui, Shiyao, et al.
Published: (2025)
Guiding not Forcing: Enhancing the Transferability of Jailbreaking Attacks on LLMs via Removing Superfluous Constraints
by: Yang, Junxiao, et al.
Published: (2025)
by: Yang, Junxiao, et al.
Published: (2025)
Agent-SafetyBench: Evaluating the Safety of LLM Agents
by: Zhang, Zhexin, et al.
Published: (2024)
by: Zhang, Zhexin, et al.
Published: (2024)
From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks
by: Zhang, Zhexin, et al.
Published: (2024)
by: Zhang, Zhexin, et al.
Published: (2024)
Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization
by: Zhang, Zhexin, et al.
Published: (2023)
by: Zhang, Zhexin, et al.
Published: (2023)
The Missing Half: Unveiling Training-time Implicit Safety Risks Beyond Deployment
by: Zhang, Zhexin, et al.
Published: (2026)
by: Zhang, Zhexin, et al.
Published: (2026)
ShieldVLM: Safeguarding the Multimodal Implicit Toxicity via Deliberative Reasoning with LVLMs
by: Cui, Shiyao, et al.
Published: (2025)
by: Cui, Shiyao, et al.
Published: (2025)
How Should We Enhance the Safety of Large Reasoning Models: An Empirical Study
by: Zhang, Zhexin, et al.
Published: (2025)
by: Zhang, Zhexin, et al.
Published: (2025)
Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
by: Zhou, Huichi, et al.
Published: (2025)
by: Zhou, Huichi, et al.
Published: (2025)
LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety
by: Yang, Junxiao, et al.
Published: (2026)
by: Yang, Junxiao, et al.
Published: (2026)
BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs
by: Yang, Junxiao, et al.
Published: (2025)
by: Yang, Junxiao, et al.
Published: (2025)
LongSafety: Evaluating Long-Context Safety of Large Language Models
by: Lu, Yida, et al.
Published: (2025)
by: Lu, Yida, et al.
Published: (2025)
UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset
by: Wang, Haoyu, et al.
Published: (2024)
by: Wang, Haoyu, et al.
Published: (2024)
Aloe: A Family of Fine-tuned Open Healthcare LLMs
by: Gururajan, Ashwin Kumar, et al.
Published: (2024)
by: Gururajan, Ashwin Kumar, et al.
Published: (2024)
AISafetyLab: A Comprehensive Framework for AI Safety Evaluation and Improvement
by: Zhang, Zhexin, et al.
Published: (2025)
by: Zhang, Zhexin, et al.
Published: (2025)
ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors
by: Zhang, Zhexin, et al.
Published: (2024)
by: Zhang, Zhexin, et al.
Published: (2024)
JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering
by: Chen, Renmiao, et al.
Published: (2025)
by: Chen, Renmiao, et al.
Published: (2025)
Data-efficient LLM Fine-tuning for Code Generation
by: Lv, Weijie, et al.
Published: (2025)
by: Lv, Weijie, et al.
Published: (2025)
Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach
by: Li, Dongyue, et al.
Published: (2024)
by: Li, Dongyue, et al.
Published: (2024)
EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
by: Huang, Dong, et al.
Published: (2024)
by: Huang, Dong, et al.
Published: (2024)
Topic Modeling with Fine-tuning LLMs and Bag of Sentences
by: Schneider, Johannes
Published: (2024)
by: Schneider, Johannes
Published: (2024)
Fine-tuning and Utilization Methods of Domain-specific LLMs
by: Jeong, Cheonsu
Published: (2024)
by: Jeong, Cheonsu
Published: (2024)
Fine-tuning Done Right in Model Editing
by: Yang, Wanli, et al.
Published: (2025)
by: Yang, Wanli, et al.
Published: (2025)
When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications
by: Liu, Qidong, et al.
Published: (2023)
by: Liu, Qidong, et al.
Published: (2023)
Can LLMs Predict Citation Intent? An Experimental Analysis of In-context Learning and Fine-tuning on Open LLMs
by: Koloveas, Paris, et al.
Published: (2025)
by: Koloveas, Paris, et al.
Published: (2025)
IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation
by: Wen, Bosi, et al.
Published: (2025)
by: Wen, Bosi, et al.
Published: (2025)
Token-level Data Selection for Safe LLM Fine-tuning
by: Li, Yanping, et al.
Published: (2026)
by: Li, Yanping, et al.
Published: (2026)
RLSF: Fine-tuning LLMs via Symbolic Feedback
by: Jha, Piyush, et al.
Published: (2024)
by: Jha, Piyush, et al.
Published: (2024)
Disentangling Reasoning Tokens and Boilerplate Tokens For Language Model Fine-tuning
by: Ye, Ziang, et al.
Published: (2024)
by: Ye, Ziang, et al.
Published: (2024)
Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
by: Zhang, Zhixin, et al.
Published: (2025)
by: Zhang, Zhixin, et al.
Published: (2025)
Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs
by: Christophe, Clément, et al.
Published: (2024)
by: Christophe, Clément, et al.
Published: (2024)
Agent Fine-tuning through Distillation for Domain-specific LLMs in Microdomains
by: Xue, Yawen, et al.
Published: (2025)
by: Xue, Yawen, et al.
Published: (2025)
Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models
by: Wang, Yu, et al.
Published: (2025)
by: Wang, Yu, et al.
Published: (2025)
Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets
by: Li, Dongyue, et al.
Published: (2025)
by: Li, Dongyue, et al.
Published: (2025)
On Active Privacy Auditing in Supervised Fine-tuning for White-Box Language Models
by: Sun, Qian, et al.
Published: (2024)
by: Sun, Qian, et al.
Published: (2024)
Two Intermediate Translations Are Better Than One: Fine-tuning LLMs for Document-level Translation Refinement
by: Dong, Yichen, et al.
Published: (2025)
by: Dong, Yichen, et al.
Published: (2025)
Learning or Self-aligning? Rethinking Instruction Fine-tuning
by: Ren, Mengjie, et al.
Published: (2024)
by: Ren, Mengjie, et al.
Published: (2024)
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
ITERTL: An Iterative Framework for Fine-tuning LLMs for RTL Code Generation
by: Wu, Peiyang, et al.
Published: (2024)
by: Wu, Peiyang, et al.
Published: (2024)
Preference-grounded Token-level Guidance for Language Model Fine-tuning
by: Yang, Shentao, et al.
Published: (2023)
by: Yang, Shentao, et al.
Published: (2023)
Similar Items
-
When Smiley Turns Hostile: Interpreting How Emojis Trigger LLMs' Toxicity
by: Cui, Shiyao, et al.
Published: (2025) -
Guiding not Forcing: Enhancing the Transferability of Jailbreaking Attacks on LLMs via Removing Superfluous Constraints
by: Yang, Junxiao, et al.
Published: (2025) -
Agent-SafetyBench: Evaluating the Safety of LLM Agents
by: Zhang, Zhexin, et al.
Published: (2024) -
From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks
by: Zhang, Zhexin, et al.
Published: (2024) -
Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization
by: Zhang, Zhexin, et al.
Published: (2023)