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”.

The profound transformation of the knowledge ecosystem and technological environment, along with the deepening evolution of library services, has driven continuous advancements in the mission of librarians. The new missions of libraries include roles such as literacy cultivators, research collaborators, community connectors, experience designers,digital literature preservers, and advocates of open science. This article will focus on three key directions—digital transformation, multidimensional literacy, and open science—to connect the future development of libraries from the perspective of these new missions. Aligning with the phased goals for 2035, it proposes that libraries should become learning hubs in the digital society, spaces for cultivating civic literacy, and intermediary platforms for open science. Through phased planning of action routes, it envisions how librarians can shape a new paradigm of knowledge sharing with professional dedication and social responsibility in a future where intelligence and humanity coexist.

With the rapid advancement of information technology, the development of smart libraries has become a core task and strategic direction for the transformation and development of the global library field. This paper,grounded in the context of smart library development being elevated to a national strategy during the 14th Five-Year Plan period, delves into the shift in smart library evaluation paradigms—from performance evaluation focused on efficiency to effectiveness evaluation emphasizing tangible outcomes. It systematically reviews the development of public library evaluation in China and its role in driving technological adoption. It distinguishes between performance evaluation and effectiveness evaluation by examining their core concepts, theoretical foundations, and international practices. Furthermore, it constructs a comprehensive evaluation framework encompassing multiple dimensions:smart spaces, smart services, smart resources, smart management, and smart librarians. Drawing on representative domestic and international case studies, this paper analyzes the key technologies, practical achievements, and challenges currently facing smart library development. It aims to provide theoretical references and practical pathways for the scientific evaluation and sustainable development of future smart libraries, ultimately driving the professional advancement of library services through management empowerment. This will enable libraries to demonstrate their irreplaceable social value in the era of digital intelligence.

AI literacy exhibits distinct characteristics of interdisciplinary integration, with the rich resource endowments of libraries serving as the core foundation for its educational implementation. Through a systematic analysis of theoretical frameworks and typical cases of AI literacy instruction, this study finds that AI literacy is not a static list of competencies and a collection of knowledge, but rather an open system that is continuously reconstructed alongside technological evolution. Leveraging the resource advantages of libraries, strengthening top-level design, and constructing a systematic educational framework within this dynamic evolution are pivotal to the standardized development of AI literacy education in libraries.

The rapid development of generative artificial intelligence (GAI) presents a strategic opportunity for the intelligent transformation of libraries. However, there is a clear disconnect between current research and practice at the project decision-making level: libraries generally lack meso-level analytical tools to assess the feasibility and strategic fit of AI projects, leading to fragmented innovation paths, resource misallocation, and strategic anxiety. Focusing on academic library settings, this study constructs an AI innovation project evaluation framework that encompasses five dimensions:technical difficulty, cost threshold, compliance risk, user value, and strategic window. On the basis of clarifying the definitions and assessment content of each dimension, the framework is applied to two typical cases—“AI-based scholarly search” and “AI literacy education”—to systematically demonstrate its practical use in project analysis and decision trade-offs, and to summarize a phased, iterative evaluation process and project categorization strategy. The findings show that this framework can help libraries identify quick-win projects, strategic projects, and cautious projects among multiple options, thus enabling a shift in decision-making from “whether to introduce AI” to “how to select and implement AI in a scientifically grounded way”. The results provide theoretical support and practical guidance for libraries to build innovation pathways that are strategically coherent, risk-controllable, and value-sustainable in the course of intelligent transformation.

Large Language Models (LLM) is reshaping the technological landscape with a rapid momentum, and becoming a powerful engine for intelligent transformation in various domains. Driven by this technological wave, the library field has ushered in a historic opportunity for transformation.This article aims to explore the potential and possibility of the application of LLM in smart libraries. It analyzes the impact areas, impact methods, and application value of LLM in the library, summarizes the current characteristics of LLM implementation status in the library industry, and proposes application pathways and strategies. The study examines the potential AI application requirements in libraries from four aspects:services, operations, management, and space. Furthermore, it constructs and envisions the application scenarios of LLM in eight typical domains, including consulting, resource discovery, reading promotion, academic services, acquisitions and cataloging, resource processing, digital humanities, and management decision-making.

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.

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.

Artificial intelligence, a machine learning technology that aims to enhance human intelligence, will undoubtedly have a profound impact on the development of human society. Museums, as institutions that document the historical processes of human and natural development, are tasked with preserving, processing, researching, and applying a vast amount of information. This article summarizes the characteristics of this information, analyzes the traditional models of museum informatization, and proposes methods to integrate and utilize artificial intelligence concepts and technologies in museum information. Artificial intelligence technology seeks to innovate traditional museum information systems by approximating human cognitive processes and methods of utilization, overcoming the shortcomings of traditional information systems in terms of information use, application expansion, and system maintenance, thereby making information processing technology a fundamental aspect of museum work.

This paper proposes a concept for systematically managing museum data using artificial intelligence technology based on attention mechanisms and explores the technical implementation methods. Specifically, it involves integrating all museum data into a unified data warehouse and employing large language models to interpret requests expressed in natural language, translating them into programming languages capable of processing multimodal data such as images, text, and audio. These languages are then used to perform tasks such as statistical analysis, querying, summarization, and reasoning. Through the collaboration of the data layer, processing layer, and interaction layer, the system not only ensures the accuracy, completeness, and comprehensiveness of the extracted data but also derives information from data analysis, integrates information into knowledge, and ultimately develops intelligent capabilities. Additionally, it addresses the long-standing issue of data silos within various museum business systems.

The implementation of the national cultural digitization strategy and the promotion of the intelligent utilization of ancient books in the new era have put forward requirements for ancient book collection service institutions to use modern technological means to comprehensively improve the protection and dissemination capacity of ancient books. The technological development and exploration practice of the metaverse library provide a development path, theoretical support, and technical support for the collection of ancient books in the new era, and promote the reform and innovation of the work mode of ancient books. This paper reviews the development process and technical characteristics of the metaverse, and analyzes the theoretical basis, and value cognition of the metaverse to empower the work of library special collections，discusses the supporting role of metaverse technology in the construction and service of special collections of libraries from five aspects: exploring spatial reconstruction, reshaping the form of resources, providing immersive services, constructing a sharing mechanism, and cultivating professional talents, so as to make special collection resources “live”, special collection space “integrated”, and special collection services “moved”.

In recent years, while the construction of smart libraries in China has been vigorously promoted, it is also actively exploring new modes of intelligent services. Recently, large language models have attracted widespread attention from various industries due to their outstanding performance. With the open source of multiple large language models and the gradual maturity of the development paradigm of “Model as a Service (SaaS)”, smart libraries have ushered in the opportunity to upgrade their services with the help of library large language models. This paper outlines the basic concepts of large language models, proposes the basic ideas for constructing library large language models, explores the application directions of large models in the library industry, and analyzes the challenges faced by libraries in applying large language models.

In the context of increasingly tense geopolitical situations and the rapid development of artificial intelligence technology, this paper discusses the construction and support of open access resources in Chinese universities, providing a reference for safeguarding national scientific and technological security, cultural security, information security, data security, etc. The paper analyzes the development process of open resources, as well as the current status of open resource construction and utilization in domestic universities. It points out the main problems of current construction open resources in universities in terms of security and confidentiality awareness, independent control of basic platforms, core technology innovation, and resource outflow. It proposes measures and suggestions for construction and support of open resources in universities, including organizational aspects, policy norms, technological innovation, new generation open resource platforms, resource review and evaluation, resource deposit mechanism, open cooperation, etc.

The constantly changing demand of users for literature information is a normalized phenomenon. How libraries can determine the correlation between user needs and target literature transmission to improve library service efficiency is currently a problem worthy of research. Therefore, a development trend prediction method of library literature delivery services based on the LightGBM algorithm is proposed. After training the LightGBM model with the best hyperparameters,obtain the prediction development trend of library literature delivery services. The experimental results show that this method can effectively reduce the dimensionality of collected data, improve prediction efficiency, and achieve accurate prediction of the development trend of library literature delivery services.

This paper explores the coexistence and integration strategies of traditional MARC cataloging format and BIBFRAME bibliographic framework plan in the current domestic library environment. By analyzing the advantages and challenges of MARC and BIBFRAME, this paper indicates that although MARC format has strong description capabilities and high standardization, it faces the limitations of data closure and complex structure; while BIBFRAME,with its openness, semanticization, and efficient search capabilities, provides a new direction for library resource description.To address the difficulties in converting between the two formats, this paper proposes a coexistence strategy based on a core set of metadata elements, aiming to ensure the continuity of library resource description and promote book catalog data towards a more open, semantic, and efficient direction. By referring to successful international cases, such as the FOLIO platform architecture, this paper constructs a hybrid cataloging system, providing a practical path for the promotion and application of BIBFRAME in the domestic library field.

The rapid development of generative artificial intelligence (GAI) presents a strategic opportunity for the intelligent transformation of libraries. However, there is a clear disconnect between current research and practice at the project decision-making level: libraries generally lack meso-level analytical tools to assess the feasibility and strategic fit of AI projects, leading to fragmented innovation paths, resource misallocation, and strategic anxiety. Focusing on academic library settings, this study constructs an AI innovation project evaluation framework that encompasses five dimensions:technical difficulty, cost threshold, compliance risk, user value, and strategic window. On the basis of clarifying the definitions and assessment content of each dimension, the framework is applied to two typical cases—“AI-based scholarly search” and “AI literacy education”—to systematically demonstrate its practical use in project analysis and decision trade-offs, and to summarize a phased, iterative evaluation process and project categorization strategy. The findings show that this framework can help libraries identify quick-win projects, strategic projects, and cautious projects among multiple options, thus enabling a shift in decision-making from “whether to introduce AI” to “how to select and implement AI in a scientifically grounded way”. The results provide theoretical support and practical guidance for libraries to build innovation pathways that are strategically coherent, risk-controllable, and value-sustainable in the course of intelligent transformation.

Recently, DeepSeek has emerged as a phenomenal product due to its high efficiency, open-source nature, and low-cost training, fueling a nationwide AI boom. This interview explores the profound impact of the large AI model DeepSeek on the library industry. During the discussion, Mr. Liu Wei elaborated on DeepSeek’s technical advantages and analyzed its potential in library services such as knowledge provision, reference consultations, and intelligent agent applications. Mr. Liu emphasized that libraries must transform to adapt to the AI era, suggesting measures such as deploying local models, developing intelligent agents, and training readers to enhance library services. Furthermore, he pointed out that as technological and knowledge gaps continue to widen, librarians should actively embrace the changes of the times and technological advancements while steadfastly upholding their role as knowledge intermediaries.

In recent years, the exhibition services of public libraries have developed rapidly, and the application of virtual exhibitions and XR technology in exhibitions has attracted increasing attention in the field of public libraries. XR virtual exhibitions in public libraries, considering the characteristics of their exhibits and their mission, should adopt more suitable technical choices and narrative logic. This paper takes the “Reading People, Reading Cities, Reading the World” headsetbased MR virtual exhibition project of the Shanghai Library as an example. From a practical perspective, it summarizes the project's practices in three areas: project positioning, technology, and content system. It explores the reconstruction of narrative logic in this XR virtual exhibition and considers the value of XR virtual exhibitions for public libraries. This includes the unification of the textual and historical value of documents, the expansion of traditional exhibitions, and the structured transmission of historical events. The paper also reflects on issues such as the limitations of technical platforms and the high entry threshold for entering the XR era, aiming to provide new ideas for the development and future practices of virtual exhibitions.

Traditional manual cataloging models are facing sustainability bottlenecks amid the explosive growth in the scale and diversity of information resources, becoming a critical constraint on library knowledge services. While generative artificial intelligence offers new technological opportunities for automated metadata creation, existing explorations often suffer from insufficient workflow integration, difficulties in quality control, and weak adaptability across different document types. To systematically address these challenges, this paper proposes an integrated intelligent cataloging framework for multi-type documents, incorporating fragmented AI-based cataloging practices into a scalable and implementable system. The framework provides a structured methodological foundation for the systematic adoption of large language models in library environments.Beyond proposing technical solutions adaptable to diverse document types, the framework also tackles the challenge of aligning traditional cataloging rules with AI-driven processes by introducing a dual-path mechanism of MAC and OAC, thereby resolving structural conflicts between AI technologies and cataloging standards. Finally, through case studies involving special collections on Chinese traditional opera playbills and books, the paper demonstrates the effectiveness and scalability of the proposed framework, offering both a theoretical basis and a practical paradigm for AI-driven, high-quality metadata production.

In the context of smart libraries, using intelligent methods to enhance the utilization rate of print literature and the efficiency of loan services is an important task for public libraries. By analyzing data of public libraries in Jiangsu Province from 2019 to 2023, the paper aims to provide reference strategies for improving the loan service efficiency of public libraries in China. The study found that public libraries in Jiangsu currently face challenges such as insufficient comprehensive service capabilities, concentrated service hours, documentation resources, and service group. It is recommended that public libraries can actively apply technologies such as big data and Artificial Intelligence,optimize service time and accessibility, strengthen institutional collaboration, and implement targeted reading promotion strategies to enhance the overall effectiveness of loan services.

Based on the user’s perspective, this paper explores the differences between the large language model search engine and the traditional search engine in information retrieval behavior and effectiveness, aiming to provide guidance and suggestions for the design and optimization of large language model in text content generation and return mechanism, so as to improve user experience and retrieval efficiency. Combined with questionnaire survey and observation method, this paper collects users' behavior data when using large language model search engine and traditional search engine for different retrieval tasks. Using screen recording and post-task questionnaire survey methods,records and analyzes user retrieval behavior and effectiveness indicators, and uses non-parametric test analysis to compare the differences in user retrieval behavior under different search engine environments. The research shows that compared with the traditional search engine, the large language model search engine has a long retrieval structure and less reconstruction times, the response is slow but the retrieval efficiency is high, and the result quality evaluation is insufficient but the user satisfaction is high. The research results provide directional guidance for the future evelopment and innovation path of large language model search engines,which are of great significance for promoting the continuous technological progress.

With the rapid development of artificial intelligence technology, the application of large language models in the field of library has gradually attracted attention, but there is little research on the use of large language models in library acquisition and cataloging business. This paper first introduces the main process of the acquisition and cataloging work in Shanghai library,and then analyzes the ability of large language models and the application prospects of large language models in the acquisition and cataloging business work . Through scenario examples,this paper explores the specific applications of large language models in five aspects such as the intelligent pre-selection of book lists, analysis of reader behavior and automated cataloging, and proposes a preliminary idea of integrating these applications into the library system.

This paper proposes a concept for systematically managing museum data using artificial intelligence technology based on attention mechanisms and explores the technical implementation methods. Specifically, it involves integrating all museum data into a unified data warehouse and employing large language models to interpret requests expressed in natural language, translating them into programming languages capable of processing multimodal data such as images, text, and audio. These languages are then used to perform tasks such as statistical analysis, querying, summarization, and reasoning.Through the collaboration of the data layer, processing layer, and interaction layer, the system not only ensures the accuracy,completeness, and comprehensiveness of the extracted data but also derives information from data analysis, integrates information into knowledge, and ultimately develops intelligent capabilities.Additionally, it addresses the long-standing issue of data silos within various museum business systems.

Information products are entering historical heritage at an unprecedented pace. Yet the traditional museum classification system, grounded in tangible artifacts, materiality, antiquity, and scarcity, has proven inadequate when confronted with information civilization legacies—infinitely reproducible, immaterial entities whose core value derives from intellectual paradigms. From the perspective of living archaeology, this paper proposes a bipartite framework for digital artifacts, distinguishing between intangible paradigm legacies and tangible product legacies, and constructs a unified five-level classification system (Grade I–III Valuable Objects, General Objects, and Reference Objects). Through case studies of the von Neumann architecture, ENIAC, the TCP/IP protocol, original UNIX, and the first-generation iPhone, it demonstrates the theoretical validity of novel criteria including paradigm-shifting significance, Historical Milestone Significance, and irreplaceability. This standard represents a rare systematic exploration globally, providing crucial theoretical support for expanding museum collection systems from industrial to information civilization, with practical implications for collection expansion, exhibition narrative renewal, and digital heritage protection policy formulation.

The profound transformation of the knowledge ecosystem and technological environment, along with the deepening evolution of library services, has driven continuous advancements in the mission of librarians. The new missions of libraries include roles such as literacy cultivators, research collaborators, community connectors, experience designers,digital literature preservers, and advocates of open science. This article will focus on three key directions—digital transformation, multidimensional literacy, and open science—to connect the future development of libraries from the perspective of these new missions. Aligning with the phased goals for 2035, it proposes that libraries should become learning hubs in the digital society, spaces for cultivating civic literacy, and intermediary platforms for open science. Through phased planning of action routes, it envisions how librarians can shape a new paradigm of knowledge sharing with professional dedication and social responsibility in a future where intelligence and humanity coexist.

This paper systematically analyzes the core challenges faced by artificial intelligence technologies, particularly large language models (LLMs), in museum applications. By examining the structural limitations inherent in LLMs, it further explores the practical difficulties encountered by museums when implementing AI. In response to these issues,systematic countermeasures and a tiered governance framework are proposed to provide methodological support for the controlled implementation of AI in the cultural heritage sector. The study demonstrates that through prudent planning and scientific governance, artificial intelligence can serve as an effective tool to enhance the core operational capabilities of museums, offering sustainable momentum for innovation in cultural heritage preservation, research, and public services.

AI literacy exhibits distinct characteristics of interdisciplinary integration, with the rich resource endowments of libraries serving as the core foundation for its educational implementation. Through a systematic analysis of theoretical frameworks and typical cases of AI literacy instruction, this study finds that AI literacy is not a static list of competencies and a collection of knowledge, but rather an open system that is continuously reconstructed alongside technological evolution. Leveraging the resource advantages of libraries, strengthening high-level institutional design, and constructing a systematic educational framework within this dynamic evolution are pivotal to the standardized development of AI literacy education in libraries.

As LLM evolve from generative AI toward AI agents capable of independent planning and action, the governance challenges posed by their autonomy—such as blurred accountability and uncertain risks—have become increasingly prominent. Taking EU and US regulations on AI agents as its research object and adopting a comparative analysis method, this paper first defines the core characteristics of AI agents from three dimensions: action autonomy, risk uncertainty, and liability ambiguity, and provides a 3‑dimensional analytical framework covering “timing of regulatory intervention, rules of responsibility allocation, and boundaries of intervention capacity.” On this basis, it systematically compares the EU’s risk‑based, ex‑ante preventive model, with the US’s innovation‑friendly, ex‑post approach. The findings show that while existing EU and US regulations can provide some effective oversight of AI agents, they face growing inadequacies: the EU model suffers from a “human‑supervision paradox,” while the US model encounters a “black‑box accountability problem” in multi‑agent collaborative scenarios. Therefore, this paper proposes that China should absorb the legal certainty of the EU model and the regulatory flexibility of the US model, pursuing a middle path characterized by tiered classification, clear accountability, traceability, and dynamic adaptability, so as to provide theoretical guidance for AI governance in the age of agents.

As the native heritage of information civilization, digital artifacts face preservation and conservation challenges fundamentally distinct from those confronting traditional material cultural heritage. Traditional cultural heritage conservation centers on material analysis, deterioration identification, and physicochemical intervention, adhering to the three principles of minimal intervention, reversibility, and prevention. By contrast, digital artifacts, as "dependent life forms," do not suffer from deterioration from intrinsic material decay; rather, their deterioration stems from the external rupture of preservation environments, storage media, and ecological chains. Grounded in the methodology of living archaeology and extending the dual-track classification system of digital artifacts, this paper proposes the core thesis that "preservation is conservation," arguing that its scope is strictly limited to intangible paradigm legacies and software-based tangible products. It then constructs a dual-track conservation framework centered on ecological-chain preservation, presenting specific methods including emulation, migration, encapsulation, and Docker containerization. Simultaneously, responding to the conservation needs of hardware-based tangible product legacies, it advances a parallel-track strategy of "traditional conservation plus ecological-chain preservation." Meanwhile, only by embedding digital artifacts within a dynamic ecological chain can their cultural value and historical significance as living heritage be sustained.