Liu, Tianci, Li, Ruirui, Qi, Yunzhe, Liu, Hui, Tang, Xianfeng, Yin, Qingyu, Cheng, Monica Xiao, Huan, Jun, Wang, Haoyu, and Gao, Jing. Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning. Retrieved from https://par.nsf.gov/biblio/10647643.

Liu, Tianci, Li, Ruirui, Qi, Yunzhe, Liu, Hui, Tang, Xianfeng, Yin, Qingyu, Cheng, Monica Xiao, Huan, Jun, Wang, Haoyu, & Gao, Jing. Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning. Retrieved from https://par.nsf.gov/biblio/10647643.

Liu, Tianci, Li, Ruirui, Qi, Yunzhe, Liu, Hui, Tang, Xianfeng, Yin, Qingyu, Cheng, Monica Xiao, Huan, Jun, Wang, Haoyu, and Gao, Jing. "Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning". Country unknown/Code not available: Proceedings of the Thirteenth International Conference on Learning Representations. https://par.nsf.gov/biblio/10647643.

@article{osti_10647643,
place = {Country unknown/Code not available}, title = {Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning}, url = {https://par.nsf.gov/biblio/10647643}, abstractNote = {}, journal = {}, publisher = {Proceedings of the Thirteenth International Conference on Learning Representations}, author = {Liu, Tianci and Li, Ruirui and Qi, Yunzhe and Liu, Hui and Tang, Xianfeng and Yin, Qingyu and Cheng, Monica Xiao and Huan, Jun and Wang, Haoyu and Gao, Jing}, }