CONVERSATIONAL

作品数：90被引量：34H指数：2
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Correction to: MOSS: An Open Conversational Large Language Model
《Machine Intelligence Research》2024年第6期1216-1216,共1页Tianxiang Sun Xiaotian Zhang Zhengfu He Peng Li Qinyuan Cheng Xiangyang Liu Hang Yan Yunfan Shao Qiong Tang Shiduo Zhang Xingjian Zhao Ke Chen Yining Zheng Zhejian Zhou Ruixiao Li Jun Zhan Yunhua Zhou Linyang Li Xiaogui Yang Lingling Wu Zhangyue Yin Xuanjing Huang Yu-Gang Jiang Xipeng Qiu 
Correction to: MOsS: An Open Conversational LargeLanguage ModelDOI:10.1007/s11633-024-1502-8Authors: Tianxiang Sun, Xiaotian Zhang, Zhengfu He,Peng Li, Qinyuan Cheng, Xiangyang Liu, Hang Yan,Yunfan Shao, Qiong Tang, S...
关键词：OPEN CORRECTION Xiang 
MOSS:An Open Conversational Large Language Model被引量：2
《Machine Intelligence Research》2024年第5期888-905,共18页Tianxiang Sun Xiaotian Zhang Zhengfu He Peng Li Qinyuan Cheng Xiangyang Liu Hang Yan Yunfan Shao Qiong Tang Shiduo Zhang Xingjian Zhao Ke Chen Yining Zheng Zhejian Zhou Ruixiao Li Jun Zhan Yunhua Zhou Linyang Li Xiaogui Yang Lingling Wu Zhangyue Yin Xuanjing Huang Yu-Gang Jiang Xipeng Qiu 
supported by the National Natural Science Foundation of China(No.62022027).
Conversational large language models(LLMs)such as ChatGPT and GPT-4 have recently exhibited remarkable capabilities across various domains,capturing widespread attention from the public.To facilitate this line of rese...
关键词：Large language models natural language processing pre-training ALIGNMENT chatGPT MOSS 
GraphFlow+:Exploiting Conversation Flow in Conversational Machine Comprehension with Graph Neural Networks
《Machine Intelligence Research》2024年第2期272-282,共11页Jing Hu Lingfei Wu Yu Chen Po Hu Mohammed J.Zaki 
The conversation machine comprehension(MC)task aims to answer questions in the multi-turn conversation for a single passage.However,recent approaches don’t exploit information from historical conversations effectivel...
关键词：Conversational machine comprehension(MC) reading comprehension question answering graph neural networks(GNNs) natural language processing(NLP) 
How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges被引量：1
《Machine Intelligence Research》2023年第5期605-613,共9页Haotong Qin Ge-Peng Ji Salman Khan Deng-Ping Fan Fahad Shahbaz Khan Luc Van Gool 
Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI.Notably,Bard has recently been updated to handle visual inputs alongside text prompts during conversations.Giv...
关键词：Google Bard multi-modal understanding visual comprehension large language models conversational AI chatbot. 
EVA2.0:Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training被引量：2
《Machine Intelligence Research》2023年第2期207-219,共13页Yuxian Gu Jiaxin Wen Hao Sun Yi Song Pei Ke Chujie Zheng Zheng Zhang Jianzhu Yao Lei Liu Xiaoyan Zhu Minlie Huang 
supported by the 2030 National Key AI Program of China(No.2021ZD0113304);the National Science Foundation for Distinguished Young Scholars(No.62125604);the NSFC projects(Key project with No.61936010 and regular project with No.61876096);the Guoqiang Institute of Tsinghua University,China(Nos.2019GQG1 and 2020GQG0005);Tsinghua-Toyota Joint Research Fund.
Large-scale pre-training has shown remarkable performance in building open-domain dialogue systems.However,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue ...
关键词：Natural language processing deep learning(DL) large-scale pre-training dialogue systems Chinese open-domain conversational model 
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