Machine Intelligence Research

目录

Vol.20, No.2

  Editorial

Editorial for Special Issue on Large-scale Pre-training: Data, Models, and Fine-tuning

Ji-Rong Wen, Zi Huang & Hanwang Zhang

https://link.springer.com/article/10.1007/s11633-023-1431-y

https://www.mi-research.net/en/article/doi/10.1007/s11633-023-1431-y

Pre-training in Medical Data: A Survey

Yixuan Qiu, Feng Lin, Weitong Chen, Miao Xu

https://link.springer.com/article/10.1007/s11633-022-1382-8

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1382-8

中文导读：

精选综述 | 医学数据预训练

Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-level Backdoor Attacks

Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, Maosong Sun

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1377-5

https://link.springer.com/article/10.1007/s11633-022-1377-5

A Study of Using Synthetic Data for Effective Association Knowledge Learning

Yuchi Liu, Zhongdao Wang, Xiangxin Zhou, Liang Zheng

https://link.springer.com/article/10.1007/s11633-022-1380-x

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1380-x

中文导读：

专题好文 | 利用合成数据进行有效关联知识学习的研究

  研究论文∣清华大学黄民烈团队

EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training

Yuxian Gu, Jiaxin Wen, Hao Sun, Yi Song, Pei Ke, Chujie Zheng, Zheng Zhang, Jianzhu Yao, Lei Liu, Xiaoyan Zhu, Minlie Huang

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1387-3

https://link.springer.com/article/10.1007/s11633-022-1387-3

  研究论文∣中国人民大学金琴团队

Multimodal Pretraining from Monolingual to Multilingual

Liang Zhang, Ludan Ruan, Anwen Hu, Qin Jin

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1414-4

https://link.springer.com/article/10.1007/s11633-022-1414-4

Offline Pre-trained Multi-agent Decision Transformer

Linghui Meng, Muning Wen, Chenyang Le, Xiyun Li, Dengpeng Xing, Weinan Zhang, Ying Wen, Haifeng Zhang, Jun Wang, Yaodong Yang, Bo Xu

https://link.springer.com/article/10.1007/s11633-022-1383-7

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1383-7

Compositional Prompting Video-language Models to Understand Procedure in Instructional Videos

Guyue Hu, Bin He, Hanwang Zhang

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1409-1

https://link.springer.com/article/10.1007/s11633-022-1409-1

Mitigating Spurious Correlations for Self-supervised Recommendation

Xin-Yu Lin, Yi-Yan Xu, Wen-Jie Wang, Yang Zhang, Fu-Li Feng

https://link.springer.com/article/10.1007/s11633-022-1374-8

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1374-8

中文导读：

https://mp.weixin.qq.com/s/Ig3jy1LulUsxoO8kjSQU8g

DynamicRetriever: A Pre-trained Model-based IR System Without an Explicit Index

Yu-Jia Zhou, Jing Yao, Zhi-Cheng Dou, Ledell Wu, Ji-Rong Wen

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1373-9

https://link.springer.com/article/10.1007/s11633-022-1373-9

Vision Enhanced Generative Pre-trained Language Model for Multimodal Sentence Summarization

Liqiang Jing, Yiren Li, Junhao Xu, Yongcan Yu, Pei Shen, Xuemeng Song

https://www.mi-research.net/en/article/doi/10.1007/s11633-022-1372-x

https://link.springer.com/article/10.1007/s11633-022-1372-x

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∨关于Machine Intelligence Research

Machine Intelligence Research（简称MIR，原刊名International Journal of Automation and Computing）由中国科学院自动化研究所主办，于2022年正式出版。MIR立足国内、面向全球，着眼于服务国家战略需求，刊发机器智能领域最新原创研究性论文、综述、评论等，全面报道国际机器智能领域的基础理论和前沿创新研究成果，促进国际学术交流与学科发展，服务国家人工智能科技进步。期刊入选"中国科技期刊卓越行动计划"，已被ESCI、EI、Scopus、中国科技核心期刊、CSCD等数据库收录。

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