Social character, as a product of the interaction between individuals and society, encompasses three dimensions:material self, social self, and spiritual self, reflecting the individual’s life priorities and value pursuits. This study takes the 2019 library borrowing data across various districts of Shanghai as a lens to examine the reading preferences of local residents and their corresponding social character traits, as well as the interactions between these traits and also explores the influence of dimensions such as region and age on social character. The BERTopic model is employed for topic clustering,and two-way ANOVA is applied to conduct a statistical analysis of the social character traits across different districts and age groups. It was found that the stage of regional development is closely related to social character traits. Residents in central districts tend to prioritize the spiritual self, whereas those in suburban or economically developed areas place more emphasis on the material self and social self. Age also has a significant impact on individual social character, with adolescents,adults, and elderly groups showing greater concern for the spiritual self, social self, and material self, respectively. Furthermore, residents’ social character is also influenced by the interaction between age and regional factors.

As one of the core parts of the ancient Chinese political system, the system of prime ministers is an important tool for exploring the top-level institutional design of the ancient China and deepening the understanding of the operation of the ancient regime. At present, there are a lot of researches related to prime ministers, but they are mostly focused on the whole system, with less consideration of geography as an important influence factor, and lack of trajectory portrayal of the changes in the positions of the prime ministers since they joined the civil service. This paper takes the prime ministers of the Song Dynasty as an example, and based on the database of Chinese biographies and historical documents, systematically analyzes the career changes and geographic distribution of prime ministers, and constructs a map system of the trajectories of Chinese prime ministers. Through the complete interactive map of prime ministers’ career trajectories and the website search function, the research provides an intuitive research and learning tool for historians, geographers and the public, which helps to deepen the understanding of the political geography of ancient China, and provides methodological support for the in-depth application of the Historical Geographic Information System (HGIS) to the study of humanities fields.

During the Republican era in China, libraries and museums maintained a close and intertwined relationship, shaped by both foreign influences and indigenous factors. This article adopts a historical research approach to trace the transnational trajectory of the concept of “library-museum integration”—originating in the United Kingdom, transplanted to Japan, and subsequently introduced to China, where it underwent localized transformation. Under the influence of various educational ideologies including auxiliary education, social education, vocational training, and new democratic cultural education—the concept of “library-museum integration” in China manifested in several distinctive forms, including dual-purpose institutions, parallel development, scholarly community, and interdisciplinary academic programs. The article argues that institutional inertia rooted in aristocratic traditions played a key role in shaping the British model of “library-museum integration”. In Japan, driven by industrial development, the concept was functionally restructured. In the Chinese context, educational factors proved decisive in the evolution of the concept of “library-museum integration” in modern China.

In the context of the era of Digital Intelligence and Humanities, the paper discusses in depth the challenges encountered by the humanities, the integration and development of GLAMS and their mission of the times. Driven by the scientific and technological revolution, the integration of GLAMS has become a trend, and they show competition and integration in the public cultural service sector. The mutual integration of GLAMS not only promotes the dissemination and acquisition of knowledge, but also gives rise to the emergence and development of new knowledge. Modern information technology provides GLAMS with an eternal space that transcends physical boundaries and material life, so that the information and values they carry can be disseminated and passed on eternally. The paper points out the important role of GLAMS in the era of Digital Intelligence, including the preservation, dissemination and utilisation of cultural heritage resources, as well as the exploration of ultimate human problems.

With the rapid advancement and widespread application of artificial intelligence (AI) technology, libraries-an essential institution for knowledge preservation and public service-are encountering unprecedented opportunities and profound challenges. AI holds the potential to significantly enhance operational efficiency and deliver more personalized,intelligent services to users. However, issues such as industry transformation, practical difficulties in technology implementation, and the adaptation of librarians’ skills have also emerged as pressing concerns for the library sector.This paper draws on the core discussions from the Directors’ Forum at the 21st Advanced Digital Library Seminar (ADLS 2025) and integrates insights from the industry and the academic to systematically explore new development pathways and strategies for libraries in the AI era, covering dimensions such as resource development, service models, spatial design, and professional competencies. The study aims to provide theoretical references and practical guidance for libraries undergoing transformation in this new era, ensuring their sustainable development and value redefinition amid the AI wave while maintaining their critical role in an intelligent information environment.

With the rapid development of artificial intelligence and large model technologies, the global library industry is gradually integrating these technologies into business processes and user services. As a key technical architecture, AI agents not only address the shortcomings of large models in library business understanding and tool cognition but also provide an important technical path for the intelligent development of library industry goals and tasks through the combination of domain expertise and data. This article showcases the value of AI agent technology in optimizing business processes and enhancing user experience by investigating the intelligent practices of libraries at home and abroad, as well as the application of AI agents in other industries such as publishing, museums, and education. The article first analyzes the recent trends in AI agent technology development and the problems encountered when existing large model technologies are applied in real-world scenarios. Then, it discusses how the existing AI agent application experiences can provide insights for library innovation and summarizes the paths for applying AI agents in optimizing business processes. Finally, the article proposes a framework for optimizing library business processes based on the AI agent architecture and introduces a preliminaryexploration of applying AI agents to a specific scenario, “Duty Assistant.” It analyzes the potential application of AI agents in libraries in the future. The research in this article indicates that AI agent technology can drive the intelligent transformation of libraries, achieve seamless integration of new te。chnologies with traditional systems, and lay a solid foundation for future knowledge services.

Addressing the static limitations in the study of the evolution of Chinese painting theory, this research employs digital humanities technologies to analyze the patterns of conceptual evolution and the mechanisms of artistic innovation.Based on over 1 400 pieces of painting theory literature from the pre-Qin period to the Ming and Qing dynasties, a four-dimensional evaluation system was constructed using text mining methods to identify frequent terms. The TF-IDF algorithm was used to detect hot terms, and a hotspot index was established based on term weights. Through diachronic novelty and intergenerational inheritance analysis, new terms were identified, and a vitality index was created based on the mean weight of new terms. The study found that 23 high-frequency core categories, such as “brush” “ink” “mountain” and “water” form a cluster of (trans-temporal) concepts. Their evolution exhibits three distinct stages: the pre-Tang system of form and spirit realism, the Song-Yuan shift towards expressive abstraction, and the Ming-Qing period of stylistic rigidity. Artistic innovation follows a “double-peak decay” pattern, with the Song dynasty marking the peak of theoretical development,while the Ming and Qing dynasties fell into a vitality crisis due to technical summarization. This research provides a quantitative paradigm for analyzing traditional art theories.

Accurately grasping the current application status of AI technology in university libraries has important reference value for promoting service innovation and improving the level of intelligent services in university libraries. Using a combination of literature research, online research, and questionnaire surveys, this study aims to investigate the current application status of AI technology in university libraries and technology vendors nationwide. The results of the survey are analyzed for both achievements and problems regarding the research topic. The paper clarifies current situation of the development prospects, practical status, and implementation obstacles of AI technology in university libraries, and proposes practical suggestions to promote the development of AI technology in university libraries from three aspects: internal and external cooperation, library leaders, and librarians.

By conducting a systematic study of China’s artificial intelligence governance policies through thematic modeling and quantitative evaluation, this paper provides support and guidance for policy optimization. Effective data from the 92 nationallevel artificial intelligence governance policies issued in China from 2017 to the 15th of March, 2025 were preprocessed.The BERTopic model was used to identify policy themes, calculate keyword c-TF-IDF weights, and three other thematic indicators, and combined with policy content to conduct an in-depth analysis of governance policy priorities. Based on thematic modeling, the PMC policy evaluation model was constructed to conduct empirical quantitative analysis on nine representative policy documents. The BERTopic model identified 13 themes, covering nine key areas of China’s AI governance policies. The PMC index model indicates that the overall policy level is good, but further optimization is needed in terms of governance framework, governance tools, and governance entities. Based on this, policy recommendations were proposed, including the construction of a classified governance policy framework, the combination of policy tools, and the promotion of collaborative governance, to serve China’s AI governance practices.

The wave of large language model technologies has fostered the widespread development of generative AI (GenAI) tools and the upgrading of the knowledge service paradigm. Various organizations have chosen different upgrade paths in the face of the new window of knowledge services brought by GenAI tools. This paper analyzes the four major application directions and differentiated application trends of GenAI tools in the field of knowledge service through case studies, and points out that literature data platforms need to pay more attention to the application of GenAI tools in intelligent knowledge retrieval. Taking the construction of the AI assistant to modern literature research of “Quan Guo Bao Kan Suo Yin” as an example, the article provides a reference for the intelligent transformation of other literature database by deconstructing the upgrading paths and practical effects.

Against the backdrop of the rapid iterative development of artificial intelligence, what obvious changes will occur in an organization's knowledge management is a theoretical and practical issue worthy of study. Based on the classic SECI process model of knowledge management and Don Ihde’s human-technology relationship theory, this article explores the development trend of organizational knowledge management under artificial intelligence from multiple dimensions. The substitutability of the artificial intelligence knowledge engine will lead to the development and changes of the knowledge private domain, and organizations will pay more attention to the construction of the knowledge private domain and give rise to the path of the new apprenticeship system. The development trend of this knowledge private domain and the new apprenticeship system is expected to provide valuable inspirations for organizations to balance knowledge security and innovative vitality, and promote the in-depth study of knowledge management theory and the transformation of practice.

Artificial intelligence (AI) is reshaping scientific research paradigms at an unprecedented speed and breadth.From protein structure prediction to assisting drug development, AI technology has become an important tool in scientific research activities. However, current AI still has significant limitations in reasoning ability, knowledge generation, and experimental design, and cannot fully replace the role of human scientists. As a part of the knowledge infrastructure, the library must reposition its function and value in the scientific research ecosystem. Based on the current development trend of AI scientific applications, this article analyzes its impact and challenges on libraries, and proposes five key action strategies for the future to achieve the transformation from an “information service provider” to a “research collaborator”.

This article analyzes the reader recommendation and purchase service model and its development, and proposes a reader recommendation and purchase architecture based on a closed-loop service chain of “demand capture-human-machine processing-feedback incentives-optimization upgrade” to address the challenges of reader participation, process management,and technological ecology in traditional recommendation and purchase models. The study not only elaborates on the process design and functional characteristics of the architecture in detail, but also constructs a smart transformation path for recommendation and purchase service based on artificial intelligence technology, hoping to provide reference for the path and ecological reconstruction of traditional recommendation and purchase services, thereby further improving the service quality of library reader recommendation and purchase service and continuously releasing its effectiveness in the transformation of library services.

The development of Large Language Models (LLMs) has ushered in a democratization of Artificial Intelligence (AI) technology. With the emergence of LLMs and associated development tools, the technical barriers to AI application development have been significantly lowered, enabling individuals without technical backgrounds to participate in AI innovation. This paper chronicles librarians’ journey from observation to practice in AI development, systematically examining how librarians navigate this technological transformation. Following a trajectory from recognizing opportunities and challenges, through exploring the possibilities enabled by technology democratization, to acquiring essential tools and skills, we comprehensively map the path librarians take toward AI development. Drawing from practical experience, we propose the ESSE (Explore, Specify, Scrutinize, Enhance) methodology, a systematic AI development framework tailored for librarians with no prior coding experience. The case study of the “Open AI-Demo Workshop for Libraries” illustrates how librarians can leverage their domain expertise in conjunction with AI tools and prompt engineering to devise innovative solutions that effectively address the specific needs of libraries. This exploration not only contributes to solving long-tail demands in library operations but also highlights the evolving role and value of librarians in an era of democratized technology.

Strengthening the principal role of enterprises in technological innovation is key to enhance the overall effectiveness of the national innovation system. This paper discusses the crucial role of business intelligence analysis in enterprise technological innovation and market competition, and compares the similarities and differences between library and professional business intelligence service institutions’ service models. The article constructs a user-oriented library business intelligence analysis methodology. Through a case study of Shanghai Library's “Dermal Fillers” project, it illustrates the practical application of this methodology in actual business intelligence services, aiming to provide reference for enhancing libraries’ competitiveness and influence in the field of business intelligence services.

Taking the foreign-language red literature collection of the Renmin University of China Libraries as the research object, this study defines the concept of “foreign-language red literature”, reviews the current status of the collection,summarizes the workflow, elaborates on the research path, and analyzes the issues discovered and proposes solutions.Finally, it provides prospects for strengthening the organization, research, and utilization of foreign-language red literature in university libraries from aspects such as protection and restoration, development and utilization, and talent cultivation.

The new wave of artificial intelligence (AI) technology is profoundly propelling human society towards comprehensive transformation, and a new era of AI-driven scientific research (AI for Science) is on the horizon. The paradigm of scientific research is undergoing an unprecedented acceleration in transition. This article analyzes the concept and research significance of AI for Science, reviews the development status of AI for Science from basic disciplines such as life sciences, materials sciences, physics, mathematics, chemistry, and earth sciences, discusses the transformative role of artificial intelligence in scientific research, and explores its guiding significance for future research directions. It also discusses the challenges faced in areas such as scientific research data, ethical safety, computational resources, and talent cultivation, in order to provide strategic insights and response strategies for the future development of the scientific research field.

The proliferation of Artificial Intelligence Generated Content (AIGC) is fundamentally challenging the ontological foundations and managerial logic of Information Resource Management (IRM). Traditional IRM paradigms, predicated on a static lifecycle, prove inadequate for the extreme dynamism, emergent collaboration, and heterogeneous complexity of the AI open-source ecosystem. This paper, through an analysis of communities like Hugging Face and domestic models such as DeepSeek and Qwen, identifies three critical dimensions of generative information resources: Throughput (T),Quality (Q), and Capability Ceiling (C). Integrating insights from established theories, this paper constructs the dynamic Information Resource Management Theory (IRMT), a novel framework featuring the T-Q-C trade-off triangle to guide the strategic optimization of AI resources. This work offers more than a new theoretical paradigm for an autonomous IRM knowledge system in the AIGC era; it also delineates a practical path toward achieving efficient application of domestic AI and technological self-reliance, especially under computational constraints. Future research avenues include the quantitative modeling of the T-Q-C framework, the integration of ethical governance, and the extension of the theory to multimodal and agent-based systems.

In the context of national strategies for educational empowerment and digital China initiatives, the development of smart libraries has become a pivotal component of the national cultural digitalization strategy, necessitating artificial intelligence (AI) to drive service model innovation. This paper focuses on university library circulation and reference service scenarios, guided by the practical needs of faculty and student users. A general-purpose agent-based intelligent question-answering system was developed using a knowledge base of frequently asked questions (FAQs) in circulation operations. By integrating AI large language model to achieve automated knowledge reasoning and response generation, the system significantly enhances service efficiency while optimizing limited human resources. Empirical results demonstrate that this solution markedly improves library service effectiveness, provides a reusable technical framework for intelligent transformation in other domains, and contributes to advancing digital transformation and modernization in higher education.

We are entering an era where technology is developing at an exponential rate,and it is anticipated that the “Singularity” will arrive within the next two decades. Large language model technologies have paved possible paths for the arrival of the “Singularity”. As humanity steps into the era of “Homo Technicus”, where humans and technology deeply integrate and co-evolve, traditional humanism centered on humans faces challenges: new humans may significantly alter their nature through technological integration; machine intelligence, through self-acceleration and iteration, might develop autonomous consciousness; and the development of AI brings forth various risks and ethical issues, even concerning survival or destruction. Immediate action is necessary to incorporate the issues brought about by AI development into the research scope of the new humanities. In the next twenty years, digital humanities need to make a new turn, following the expanded new humanism, and utilize the fifth paradigm of digital humanities research (AI4DH) to evolve towards wisdom humanities.

Transformative agreements play an important role in advancing open access and open science. Compared with foreign countries, mainland universities in China have insufficient understanding of open access transformation, and carry out relatively few practices about it. This paper first analyzes the current situation of global open access transformation practice, then takes the United Kingdom, Germany and Netherlands as examples to analyze the effectiveness of transformative agreements from the dimensions of promoting open access publishing, controlling publishing costs, and improving the impact of academic achievements. Finally, this paper takes the University of Electronic Science and Technology of China as an example, and selects Cambridge University Press, RSC Press and ACM Press as representatives, which have their own characteristics on open access transformation schemes, to elaborate the specific process and precautions for individual institutions to evaluate the feasibility of implementing open access transformation. Exploring diversified transformative agreements, issuing support policies for open access publishing, providing sufficient financial guarantees, and increasing the publicity and promotion of open access publishing and open access transformation can provide strong support for the implementation of open access transformation in China.

The evolution of library information retrieval has progressed from manual card retrieval and electronic catalog retrieval to full-text retrieval. Simultaneously, the forms of library collections have undergone significant transformations,transitioning from physical collections to various databases and, ultimately, to a digital resource system encompassing diverse modalities. In the era of large language models, library information retrieval is advancing towards intelligence. Large language models can handle natural language queries from complex data sources, enhancing the retrieval methods. Based on a review of the historical development of retrieval technologies, this paper explores the enhancements brought by large language models to library information retrieval, proposes a library information retrieval system architecture based on Retrieval-Augmented Generation (RAG). It also analyzes the impact of large language models on future library information retrieval patterns.

Archives have emerged in the open science movement. The two-way interaction between open science movement and archival information services lays the scientific foundation and necessity for exploring archival information services for open science. This paper takes the four pillars mentioned in UNESCO Recommendation on Open Science,including open scientific knowledge, open scientific infrastructure, open participation, and open dialog, as a research framework, connects their conceptual connotations with the archival information service scenarios, and explores the direction of the development of archival information services in the context of open science. There are four practical scenarios for archival information services for open science: open archival knowledge service scenarios, open archival infrastructure, open public participation scenarios, and open dialogue scenarios. Providing archival information services for open science requires archives to improve the openness and sharing of archival resources, strengthen the functional construction of open archival infrastructure, build an open and participatory archival practice ecosystem, and pay attention to integrating the concept of collaboration into archival services. In the future, archives in China should adhere to the principle of dialectics and explore new development paths for archival information services in the open science movement.

In the context of rapid information technological advancement, the museum industry is undergoing profound transformation. The integration of digital technologies, particularly artificial intelligence, has not only reshaped the presentation of exhibits but also revolutionized visitor interaction experiences. Placing visitors at the center has always been a cornerstone of museum service philosophy. The development of smart guided tour systems, as a best practice of the convergence of technology and humanistic values, is leading new directions in museum education, communication,and service experiences. This paper clarifies the current state of museum guided services, the design of guided functions, and their application value. It further analyzes the challenges and proposes optimization strategies for the construction of smart guided tour systems in museums, aiming to provide insights and strategies for the sustainable development of museums.

Open Access (OA) has become an important strategy for GLAM (galleries, libraries, archives, and museums)institutions to promote cultural data sharing and facilitate public participation. This article sorts out the definition of OAwithin the context of GLAM institutions and reviews the origin and development of the Open GLAM movement. It investigates the current status of OA policies and the practices of GLAM institutions at home and abroad. Base on the analysis of the OA practices of typical GLAM institutions at home and abroad, it puts forward the suggestions and strategies for the further development of OA in GLAM institutions. In the end, the article summarizes the unique value of OA in the sharing of cultural resources, promoting public participation, innovating public cultural services, and enhancing the new quality productive forces. The aim of the article is to provide references for the sharing and dissemination of cultural resources in GLAM institutions in the digital era, importantly promoting the better implementation of OA in China's GLAM institutions to fulfill the goal of public cultural services.

As an innovative catalyst driving the integration of technology and culture, metaverse technology has pioneered new pathways for the digital transformation of the museum industry. This study takes the Shanghai Astronomy Museum as its research subject, systematically exploring the innovative applications of metaverse technology in museum management and services. By establishing a digital twin platform, the Shanghai Astronomy Museum has achieved intelligent management of venue operations, significantly enhancing operational and maintenance efficiency as well as emergency response capabilities.Through the development of the "Walking Planetarium" XR project, immersive experiences have been effectively realized,expanding the provision of high-quality science education resources. This research offers practical references for promoting the application of metaverse technology in cultural venues and provides insights for the digital transformation of museums and cultural institutions.

To understand the formation of academic figures’ relationships in the Song Dynasty and explore the integration path between digital humanities technology and traditional historical research, a Song Dynasty academic network involving 1 987 scholars and 2 742 groups of relationships was constructed based on the china biographical database(CBDB). The research focused on three core issues: the impact of scholars’ attributes (hometown, school identity,etc.) , social capital (centrality, structural holes, etc.) , and the endogenous structure of the network (reciprocity,transitivity, etc.) on the establishment of academic relationships. Geographic proximity and homogeneity of school identity have a significant positive effect on the formation of academic connections. The network shows strong reciprocity but suppressed transitivity, reflecting the bidirectionality of academic interactions and the competitive exclusion between schools. In terms of social capital, centrality, especially degree centrality and eigenvector centrality,has a significant impact on relationship building, while the role of structural holes is limited. This study provides empirical evidence for understanding the social foundation of academic dissemination in the Song Dynasty and offers a new path for the integration of digital humanities and traditional historiography.

Public libraries can deploy open-source AI Large Language Models to provide readers with engaging and easyto-use AI applications. Shanghai Library, for instance, has redeveloped a user-friendly text-to-image large language model tool using Stable Diffusion technology and organized activities for children readers to personally experience new technology of AI drawing. This innovative practice not only lowers the barrier to entry for AI usage but also stimulates children readers’interest in AI, thereby promoting the popularization of the technology. In the future, libraries can further deploy multi-modal large language models to offer more diversified services, construct a comprehensive AI literacy education system, and leverage AI large language model technology to facilitate the transformation and upgrading of libraries, enhancing their core ompetitiveness.

The Information Processing System for Chinese Characters (also known as “Project 748”) is a national key scientific and technological research project initiated by China. “Project 748” aims to change the backward situation of China’s print industry and solve the problem of computer information processing for Chinese Characters. “Project 748” has promoted the all-round development of information processing technology for Chinese Characters, and also promoted the informatization progresses of library and information cause, which is a milestone in the development history of library and information technology in China. With historical research method and network survey method, this paper systematically reviews the development history of “Project 748” and one sub project “Intelligence Search Using Chinese Characters”, analyzes its important significance in the history of library and information technology in China, and provides references for the research and development of library and information technology in China.

This paper focuses on the construction of a knowledge graph for the chronological resources of Xian Xinghai.Based on Qin Qiming’ Brief Chronicle of Xian Xinghai (1905—1945), an ontological knowledge model was developed,encompassing core entities such as persons, time, locations, events, works, and documentary sources. The Neo4j graph database was employed for data storage and relational querying, while the Vis.js library facilitated the dynamic visualization of Xian Xinghai’s social network and life trajectory. The results demonstrated that knowledge graph technology can effectively enhance the analyzability and visualization of Xian Xinghai’s life events, social networks, and artistic creation context, overcoming the limitations of traditional linear chronological representations and providing new research methods and pathways for understanding his music and revolutionary practices across different regions and stages. Future work may focus on enhancing the efficiency of knowledge extraction, expand data sources and enhance the interactive visualization experience.

Images of Modern History from the library's collection often suffer from issues such as low resolution, blurreddetails, uneven contrast, and yellowing due to long-term preservation and limitations of early photographic techniques. By analyzing the current state of image super-resolution technology, this study proposes an improved Real-ESRGAN model.Through detailed analysis of images of Modern History from the library's collection, data augmentation techniques are employed to simulate image characteristics. Additionally, multi-scale feature fusion is integrated into the RRDB module of the model, combined with a channel attention mechanism to enhance the performance of the original model. Experimental results demonstrate that the improved model significantly outperforms the original model in both overall visual quality and detail reconstruction. Specifically, the PSNR and SSIM metrics of the improved model increase by 3 dB and 0.0672, respectively, compared to the original model, making it highly suitable for super-resolution reconstruction tasks of historical library images.

This paper takes epigraphy knowledge services as an example to explore the application methods and implementation strategies of generative AI technology in digital humanities through model construction and practice.Firstly, the article expounds on the concept and characteristics of generative AI, analyzes its research status in the field of digital humanities and practical situations related to epigraphy. Secondly, it analyzes the requirements for applying generative AI to epigraphy knowledge services, involving data processing, knowledge organization and association, user services, and other aspects. Based on this, a construction model for epigraphy knowledge services based on the capabilities of generative AI technology is proposed. Finally, taking the Shanghai Library's epigraphy knowledge base as an example, the paper elaborates on the practical application of generative AI-based epigraphy knowledge services, including data processing and user services. The model proposed in this paper provides new ideas for the intelligent service of ancient books and documents such as epigraphy, achieving full-process AI empowerment from intelligent processing, handling, organizing to serving. It offers experience that can be referenced for the intelligent development of digital humanities.

With the rapid development of general artificial intelligence large model technology, humanoid robots, as a cutting-edge achievement integrating artificial intelligence and physical robotics, have attracted widespread attention.Focusing on the theme of library humanoid robots, this paper systematically reviews and analyzes their current development status and existing bottlenecks through methods including web-based survey, literature analysis, and content analysis, from multiple dimensions including academic literature, major products, and application practices. Meanwhile, by tracking the latest technological advancements and development trends, it proposes outlooks on future innovation paths and implementation strategies for library humanoid robots, aiming to provide references for the theoretical and practical development of smart libraries.

The revolution in information technology has driven profound transformations in the library industry and its information systems, with large language models exerting a disruptive impact on knowledge production and services in libraries. This paper analyzes how large models empower libraries in knowledge production, knowledge services, and knowledge experiences, and proposes that the library industry should restructure next-generation library service platforms. Based on industry research and practice, the library should formulate a roadmap for applying large models, actively promote their deep integration into technical architectures, strengthen data governance capabilities, enhance API automation platform development, and shift the overall pattern of platform architecture. At the same time, collaborative innovation within the library community will also be the key driving force behind this transformation.

This study takes the “Vessel of Knowledge” poster as an entry point to explore the innovative applications of AIGC (Artificial Intelligence Generated Content) technology in library reading promotion design. The article examines the selection and application of AIGC tools during the creation process of the “Vessel of Knowledge” poster, including theme interpretation, determining symbolic design methods, exploring and filtering visual elements, analyzing tool characteristics, prompt engineering, and optimizing details. It analyzes the effectiveness of AIGC in areas such as creative generation, visual presentation, and efficiency improvement. Based on this case, the article further explores how AIGC technology can expand from single-media design to diverse scenarios in library reading promotion. Meanwhile, it also points out the limitations of AIGC technology, such as randomness and uncontrollability of content, limited emotional and cultural expression, copyright risks, and challenges in personnel adaptability. Therefore, the study proposes strategies for libraries, including cultivating internal talent, enhancing reader interaction, integrating cultural resources and services,and fostering multi-party collaboration. In the future, the application of AIGC technology is expected to develop toward intelligence, immersion, and cross-disciplinary collaboration, potentially injecting new vitality into library reading promotion and enhancing cultural communication abilities.

In the context of the marketisation of data elements, revealing the integration mechanism between scientific data and the various elements of new quality productive forces can provide theoretical references and practical guidance for promoting the value transformation of scientific data and accelerating the development of new quality productive forces. Following the “path dimension-implementation path” framework, this paper analyses the path dimension of scientific data empowering the formation of new quality productive Forces from three horizontal dimensions: technology,institutions, and ecology. It then proposed specific implementation paths for scientific data to empower new quality productive forces from three vertical dimensions: new-type workers, new-type means of production, and new-type objects of labour. Scientific data empowers the formation of new quality productive forces through three pathways: driving innovation in research paradigms, facilitating the market-based allocation of data elements, and constructing cross-subject collaborative innovation networks. This can be achieved by enhancing the data literacy of new-quality workers, implementing legal governance of scientific data, and endowing traditional labour objects with new characteristics to empower new-quality workers, new-quality labour materials, and new-quality labour objects through scientific data.

This study targets the national security intelligence analysis scenario, aiming to overcome the informational limitations of single-modal data analysis and enhance situational awareness in complex scenarios. Based on deep learning theory, this paper constructs a heterogeneous data representation model from the macro perspective of multimodal data fusion, organizes a cross-modal data fusion framework, and introduces a dynamic weight allocation mechanism to achieve effective integration of multi-source heterogeneous data such as social media text, video, audio, satellite imagery, and network traffic. The research indicates that, in a complex data ecosystem, attention should be paid not only to the granularity of multimodal data fusion in open-source intelligence, but also to the requirements of intelligence tasks, enabling rapid and accurate fusion to form a practical and feasible industrialized process.

In the age of artificial intelligence, how to meet users’needs for information retrieval becomes a new challenge and information service platform for libraries. Retrieval-Augmented Generation (RAG) effectively solves the hallucination of large language models, which improves the accuracy and user satisfaction of intelligent retrieval applications based on large language models. On the basis of RAG models, this article has studied and constructed an intelligent retrieval system leveraging the digital resources of Quan Guo Bao Kan Suo Yin (CNBKSY). By establishing a private literature knowledge base with high-quality digital resources, and utilizing the powerful ability of large language models to understand and generate natural language, this system improves accuracy rate by integrating retrieval strategies such as query rewriting, multi-route retrieval and reranking in the form of collaboration between large language models and small neural network models.Furthermore, it has achieved the transformation of library collections from digitization to intellectualization, which further enhances the service quality of CNBKSY.

As the core carrier of the public cultural service system, public libraries face the dual challenges of precise service provision and scientific feedback mechanism under the development concept of user demand-oriented. Aiming at the current practical problems such as the single dimension of user demand identification and insufficient utilization of feedback data,this research innovatively constructs a hybrid analysis framework that integrates Bert pre-training model and LDA topic model. The Python web crawler system was used to obtain the corpus of user comments on the local internet living platform,and Bert was applied for fine-grained sentiment analysis to quantitatively analyze the spatial distribution characteristics and regional differences of user satisfaction. On this basis, a double-channel LDA topic analysis framework of affective stratification is introduced to systematically deconstruct the characteristics of user demends and emotional motivations from 31 484 valid comments. The empirical study shows that: (1) users generally hold a positive attitude towards library services, which has a slightly higher indication in the east, Hong Kong, Macao, Taiwan and central regions, and a slightly lower indication in the west and northeast regions; (2) the positive evaluation focuses on the dimensions of infrastructure intelligence, cultural resource richness and digital service innovation; (3) negative opinions mainly focus on the rationality of spatial planning and the timeliness of service response. Based on this, this paper proposes a targeted optimization path, aiming to provide data support for the improvement of user feedback mechanism and intelligent transformation of public libraries under the background of digital intelligence, and promote the sustainable optimization of public cultural institutions’ services.