Chen, Tiejin, Da, Longchao, Zhou, Huixue, Li, Pingzhi, Zhou, Kaixiong, Chen, Tianlong, and Wei, Hua. Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness. Retrieved from https://par.nsf.gov/biblio/10631239. Web. doi:10.1137/1.9781611978520.41.

Chen, Tiejin, Da, Longchao, Zhou, Huixue, Li, Pingzhi, Zhou, Kaixiong, Chen, Tianlong, & Wei, Hua. Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness. Retrieved from https://par.nsf.gov/biblio/10631239. https://doi.org/10.1137/1.9781611978520.41

Chen, Tiejin, Da, Longchao, Zhou, Huixue, Li, Pingzhi, Zhou, Kaixiong, Chen, Tianlong, and Wei, Hua. "Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness". Country unknown/Code not available: Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611978520.41. https://par.nsf.gov/biblio/10631239.

@article{osti_10631239,
place = {Country unknown/Code not available}, title = {Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness}, url = {https://par.nsf.gov/biblio/10631239}, DOI = {10.1137/1.9781611978520.41}, abstractNote = {}, journal = {}, publisher = {Society for Industrial and Applied Mathematics}, author = {Chen, Tiejin and Da, Longchao and Zhou, Huixue and Li, Pingzhi and Zhou, Kaixiong and Chen, Tianlong and Wei, Hua}, }