1 When the song Heart on My Sleeve first dropped,fans were on cloud nine,fully convinced that their favorite musicians had just dropped a surprise cooperation.But as the song racked up(累计)millions of streams online,...1 When the song Heart on My Sleeve first dropped,fans were on cloud nine,fully convinced that their favorite musicians had just dropped a surprise cooperation.But as the song racked up(累计)millions of streams online,the truth surfaced-the track was created by an Internet user who used artificial intelligence(AI)to perfectly mimic(模仿)human artists'voices.展开更多
This study explores the regeneration of Qi Baishi’s renowned shrimp paintings using artificial intelligence,guided by a systematic content analysis framework.We first deconstruct the master’s style by identifying an...This study explores the regeneration of Qi Baishi’s renowned shrimp paintings using artificial intelligence,guided by a systematic content analysis framework.We first deconstruct the master’s style by identifying and categorizing key visual elements,including line fluidity,ink intensity,dynamic expression,and negative space composition.These artistic features are then translated into descriptive labels to train a specialized Low-Rank Adaptation(LoRA)model based on a diffusion framework.The generated works are evaluated for stylistic fidelity and emotional resonance,with results indicating a high degree of similarity to Qi Baishi’s originals in morphology and dynamism.However,the study also notes limitations in the AI’s ability to replicate the nuanced subtleties of ink techniques and deeper emotional expressions.This research validates the effectiveness of content analysis in bridging traditional art aesthetics with computational generation,offering a new pathway for the preservation and innovative reinterpretation of cultural heritage.展开更多
Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is b...Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is based on technologies such as natural language processing,machine learning,and deep learning,which enable learning language rules through training models to automatically generate text that meets grammatical and semantic requirements.In this paper,we sort and systematically summarize the main research progress in text generation and review recent text generation papers,focusing on presenting a detailed understanding of the technical models.In addition,several typical text generation application systems are presented.Finally,we address some challenges and future directions in AI text generation.We conclude that improving the quality,quantity,interactivity,and adaptability of generated text can help fundamentally advance AI text generation development.展开更多
文摘1 When the song Heart on My Sleeve first dropped,fans were on cloud nine,fully convinced that their favorite musicians had just dropped a surprise cooperation.But as the song racked up(累计)millions of streams online,the truth surfaced-the track was created by an Internet user who used artificial intelligence(AI)to perfectly mimic(模仿)human artists'voices.
文摘This study explores the regeneration of Qi Baishi’s renowned shrimp paintings using artificial intelligence,guided by a systematic content analysis framework.We first deconstruct the master’s style by identifying and categorizing key visual elements,including line fluidity,ink intensity,dynamic expression,and negative space composition.These artistic features are then translated into descriptive labels to train a specialized Low-Rank Adaptation(LoRA)model based on a diffusion framework.The generated works are evaluated for stylistic fidelity and emotional resonance,with results indicating a high degree of similarity to Qi Baishi’s originals in morphology and dynamism.However,the study also notes limitations in the AI’s ability to replicate the nuanced subtleties of ink techniques and deeper emotional expressions.This research validates the effectiveness of content analysis in bridging traditional art aesthetics with computational generation,offering a new pathway for the preservation and innovative reinterpretation of cultural heritage.
基金Project supported by the National Natural Science Foundation of China(No.62272100)the Consulting Project of Chinese Academy of Engineering(No.2023-XY-09)+1 种基金the Major Project of the National Social Science Fund of China(No.21ZD11)the Fundamental Research Funds for the Central Universities,China。
文摘Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is based on technologies such as natural language processing,machine learning,and deep learning,which enable learning language rules through training models to automatically generate text that meets grammatical and semantic requirements.In this paper,we sort and systematically summarize the main research progress in text generation and review recent text generation papers,focusing on presenting a detailed understanding of the technical models.In addition,several typical text generation application systems are presented.Finally,we address some challenges and future directions in AI text generation.We conclude that improving the quality,quantity,interactivity,and adaptability of generated text can help fundamentally advance AI text generation development.
