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Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

Fuente: arXiv

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Bibliographische Detailangaben
Hauptverfasser:	Microsoft, :, Abouelenin, Abdelrahman, Ashfaq, Atabak, Atkinson, Adam, Awadalla, Hany, Bach, Nguyen, Bao, Jianmin, Benhaim, Alon, Cai, Martin, Chaudhary, Vishrav, Chen, Congcong, Chen, Dong, Chen, Dongdong, Chen, Junkun, Chen, Weizhu, Chen, Yen-Chun, Chen, Yi-ling, Dai, Qi, Dai, Xiyang, Fan, Ruchao, Gao, Mei, Gao, Min, Garg, Amit, Goswami, Abhishek, Hao, Junheng, Hendy, Amr, Hu, Yuxuan, Jin, Xin, Khademi, Mahmoud, Kim, Dongwoo, Kim, Young Jin, Lee, Gina, Li, Jinyu, Li, Yunsheng, Liang, Chen, Lin, Xihui, Lin, Zeqi, Liu, Mengchen, Liu, Yang, Lopez, Gilsinia, Luo, Chong, Madan, Piyush, Mazalov, Vadim, Mitra, Arindam, Mousavi, Ali, Nguyen, Anh, Pan, Jing, Perez-Becker, Daniel, Platin, Jacob, Portet, Thomas, Qiu, Kai, Ren, Bo, Ren, Liliang, Roy, Sambuddha, Shang, Ning, Shen, Yelong, Singhal, Saksham, Som, Subhojit, Song, Xia, Sych, Tetyana, Vaddamanu, Praneetha, Wang, Shuohang, Wang, Yiming, Wang, Zhenghao, Wu, Haibin, Xu, Haoran, Xu, Weijian, Yang, Yifan, Yang, Ziyi, Yu, Donghan, Zabir, Ishmam, Zhang, Jianwen, Zhang, Li Lyna, Zhang, Yunan, Zhou, Xiren
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Computation and Language Artificial Intelligence Machine Learning
Online-Zugang:	Acceder al recurso
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