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CASIA OpenIR

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Text Difficulty Study: Do Machines Behave the Same as Humans Regarding Text Difficulty? 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 283-293
作者:  Bowen Chen;  Xiao Ding;  Yi Zhao;  Bo Fu;  Tingmao Lin;  Bing Qin;  Ting Liu
Adobe PDF(1796Kb)  |  收藏  |  浏览/下载：3/0  |  提交时间：2024/04/23
Cognition inspired natural language processing, psycholinguistics, explainability, text difficulty, curriculum learning  
The Life Cycle of Knowledge in Big Language Models: A Survey 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 217-238
作者:  Boxi Cao;  Hongyu Lin;  Xianpei Han;  Le Sun
Adobe PDF(1430Kb)  |  收藏  |  浏览/下载：5/1  |  提交时间：2024/04/23
Pre-trained language model, knowledge acquisition, knowledge representation, knowledge probing, knowledge editing, knowledge application  
AI for Supporting the Freedom of Drawing 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 63-88
作者:  Xiaohua Sun;  Juexiao Qin
Adobe PDF(14055Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/04/23
Intention understanding, drawing support, drawing, art, human-artificial intelligence (AI) collaboration  
Cogeneration of Innovative Audio-visual Content: A New Challenge for Computing Art 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 4-28
作者:  Mengting Liu;  Ying Zhou;  Yuwei Wu;  Feng Gao
Adobe PDF(14438Kb)  |  收藏  |  浏览/下载：1/0  |  提交时间：2024/04/23
Artificial intelligence (AI) art, audio-visual, artificial intelligence generated content (AIGC), multimodal, artistic evaluation  
How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 605-613
作者:  Haotong Qin;   Ge-Peng Ji;  Salman Khan;  Deng-Ping Fan;  Fahad Shahbaz Khan;  Luc Van Gool
Adobe PDF(10373Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/04/23
Google Bard, multi-modal understanding, visual comprehension, large language models, conversational AI, chatbot  
Transformer: A General Framework from Machine Translation to Others 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 514-538
作者:  Yang Zhao;  Jiajun Zhang;  Chengqing Zong
Adobe PDF(1415Kb)  |  收藏  |  浏览/下载：4/0  |  提交时间：2024/04/23
Neural machine translation, Transformer, document neural machine translation (NMT), multimodal NMT, low-resource NMT  
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 447-482
作者:  Xiao Wang;  Guangyao Chen;  Guangwu Qian;  Pengcheng Gao;  Xiao-Yong Wei;  Yaowei Wang;  Yonghong Tian;  Wen Gao
Adobe PDF(3540Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/04/23
Multi-modal (MM), pre-trained model (PTM), information fusion, representation learning, deep learning  
A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-oriented Dialogue Policy Learning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 318-334
作者:  Wai-Chung Kwan;  Hong-Ru Wang;  Hui-Min Wang;  Kam-Fai Wong
Adobe PDF(2211Kb)  |  收藏  |  浏览/下载：0/0  |  提交时间：2024/04/23
Dialogue policy learning (DPL), task-oriented dialogue system (TOD), reinforcement learning (RL), dialogue system, Markov decision process  
Vision Enhanced Generative Pre-trained Language Model for Multimodal Sentence Summarization 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 289-298
作者:  Liqiang Jing;  Yiren Li;  Junhao Xu;  Yongcan Yu;  Pei Shen;  Xuemeng Song
Adobe PDF(2389Kb)  |  收藏  |  浏览/下载：4/0  |  提交时间：2024/04/23
Multimodal sentence summarization (MMSS)  generative pre-trained language model (GPLM)  natural language generation  deep learning  artificial intelligence  
EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 207-219
作者:  Yuxian Gu;  Jiaxin Wen;  Hao Sun;  Yi Song;  Pei Ke;  Chujie Zheng;  Zheng Zhang;  Jianzhu Yao;  Lei Liu;  Xiaoyan Zhu;  Minlie Huang
Adobe PDF(1846Kb)  |  收藏  |  浏览/下载：2/1  |  提交时间：2024/04/23
Natural language processing  deep learning (DL)  large-scale pre-training  dialogue systems  Chinese open-domain conversational model