Wang, Haoyu, Li, Ruirui, Jiang, Haoming, Wang, Zhengyang, Tang, Xianfeng, Bi, Bin, Cheng, Monica, Yin, Bing, Wang, Yaqing, Zhao, Tuo, and Gao, Jing. LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. Retrieved from https://par.nsf.gov/biblio/10483535.

Wang, Haoyu, Li, Ruirui, Jiang, Haoming, Wang, Zhengyang, Tang, Xianfeng, Bi, Bin, Cheng, Monica, Yin, Bing, Wang, Yaqing, Zhao, Tuo, & Gao, Jing. LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. Retrieved from https://par.nsf.gov/biblio/10483535.

Wang, Haoyu, Li, Ruirui, Jiang, Haoming, Wang, Zhengyang, Tang, Xianfeng, Bi, Bin, Cheng, Monica, Yin, Bing, Wang, Yaqing, Zhao, Tuo, and Gao, Jing. "LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models". Country unknown/Code not available: KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. https://par.nsf.gov/biblio/10483535.

@article{osti_10483535,
place = {Country unknown/Code not available}, title = {LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models}, url = {https://par.nsf.gov/biblio/10483535}, abstractNote = {}, journal = {}, publisher = {KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining}, author = {Wang, Haoyu and Li, Ruirui and Jiang, Haoming and Wang, Zhengyang and Tang, Xianfeng and Bi, Bin and Cheng, Monica and Yin, Bing and Wang, Yaqing and Zhao, Tuo and Gao, Jing.}, }