2 papers
cs.AI2025
Picky LLMs and Unreliable RMs: An Empirical Study on Safety Alignment after Instruction Tuning
Guanlin Li, Kangjie Chen, Shangwei Guo +6
Large language models (LLMs) have emerged as powerful tools for addressing a wide range of general inquiries and tasks. Despite this, fine-tuning aligned LLMs on smaller, domain-sp…
cs.CV2025
Turn That Frown Upside Down: FaceID Customization via Cross-Training Data
Shuhe Wang, Xiaoya Li, Xiaofei Sun +4
Existing face identity (FaceID) customization methods perform well but are limited to generating identical faces as the input, while in real-world applications, users often desire…