2 papers
cs.CL2025
Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models
Yi Liu, Dianqing Liu, Mingye Zhu +3
The widespread adoption of large language models (LLMs) across industries has increased the demand for high-quality and customizable outputs. However, traditional alignment methods…
cs.CL2025
Mitigating Biases in Language Models via Bias Unlearning
Dianqing Liu, Yi Liu, Guoqing Jin +1
Many studies have shown various biases targeting different demographic groups in language models, amplifying discrimination and harming fairness. Recent parameter modification debi…