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20230614【面向医疗领域的基础大模型探索与应用】付杰：Cross-Lingual Multi-Modal Language Models for……
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报告嘉宾：付杰 (北京智源人工智能研究院) 报告时间：2023年06月14日 (星期三)晚上20:30 (北京时间) 报告题目：Cross-Lingual Multi-Modal Language Models for Healthcare 报告人简介： Jie Fu is a researcher at Beijing Academy of Artificial Intelligence. He received the Ph.D. degree from National University of Singapore, under the supervision of Tat-Seng Chua. He worked as a postdoc fellow with Yoshua Bengio at Quebec AI Institute (Mila), funded by Microsoft Research Montreal. He was an IVADO postdoc fellow working with Chris Pal at Quebec AI Institute (Mila). His current research interests include deep learning and large language model with their applications in NLP, CV, and other real-world tasks. He received ICLR 2021 outstanding paper award. 个人主页： https://bigaidream.github.io/ 报告摘要： Large language models have made great progress in natural language processing (NLP). This inspires researchers to apply LLMs for fields that were not considered the core playground of NLP, for example, healthcare. However, the first bottleneck for medicine using LLMs is the data, like most other breakthroughs in artificial intelligence that starts with data collection. I will first talk about our efforts in data collection and discuss frameworks we design for such tasks. 参考文献： [1] Zhongwei Wan, Che Liu, Mi Zhang, Jie Fu, Benyou Wang, Sibo Cheng, Lei Ma, César Quilodrán-Casas, Rossella Arcucci, “Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias,” arXiv:2305.19894 (2023). [2] Jianquan Li, Xidong Wang, Xiangbo Wu, Zhiyi Zhang, Xiaolong Xu, Jie Fu, Prayag Tiwari, Xiang Wan, Benyou Wang, "Huatuo-26M, a Large-scale Chinese Medical QA Dataset," arXiv:2305.01526 (2023). [3] Ge Zhang, Yemin Shi, Ruibo Liu, Ruibin Yuan, Yizhi Li, Siwei Dong, Yu Shu, Zhaoqun Li, Zekun Wang, Chenghua Lin, Wenhao Huang, Jie Fu, “Chinese Open Instruction Generalist: A Preliminary Release," arXiv:2304.07987 (2023). …………
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