12 citations · 35 across the 23 of their papers we have counts for
7 papers · 1 filter
H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMs
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +4
The alignment of pre-trained LLMs continues to draw significant attention from both industry and academia, aiming to ensure responses that are helpful, harmless, and honest. Howeve…
LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +2
Combining large language models during training or at inference time has shown substantial performance gain over component LLMs. This paper presents LLM-TOPLA, a diversity-optimize…
Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey
Tiansheng Huang, Sihao Hu, Fatih Ilhan +2
Recent research demonstrates that the nascent fine-tuning-as-a-service business model exposes serious safety concerns: fine-tuning with a few harmful data uploaded from the users c…
Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation
Tiansheng Huang, Sihao Hu, Fatih Ilhan +2
Harmful fine-tuning attack poses serious safety concerns for large language models' fine-tuning-as-a-service. While existing defenses have been proposed to mitigate the issue, thei…
Lisa: Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning Attack
Tiansheng Huang, Sihao Hu, Fatih Ilhan +2
Recent studies show that Large Language Models (LLMs) with safety alignment can be jail-broken by fine-tuning on a dataset mixed with harmful data. First time in the literature, we…
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +4
This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of pre-trained few-shot m…
A Survey on Large Language Model-Based Game Agents
Sihao Hu, Tiansheng Huang, Gaowen Liu +6
Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities…