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.

The establishment of a classification system for digital artifacts has enabled information civilization legacies to enter museum collections. Yet the traditional curatorial paradigm — grounded in material carriers, scarcity value, and static physical evidence — proves inadequate when confronted with digital artifacts, whose core characteristics are defined by the primacy of intangible paradigm, reproducibility, living-state operation, and milestone-node significance. From the perspectives of living archae logy and information civilization interpretation, and beginning with a theoretical distinction between the intellectual dimension of curation and the formal dimension of exhibition, this paper systematically demonstrates the fourfold failure of traditional curatorial paradigms in addressing digital artifacts. It then constructs the theoretical foundations, core principles, and practical models for digital artifact curation, proposing three major paradigms—logic visualization, paradigm storytelling, and executable display — along with five operational methods: emulation-based curation, principle-interactive curation, paradigm-evolution chain narration, interactive logic experience, and digital twin curation. This study aims to provide a systematic curatorial framework for the preservation and transmission of information civilization memory, respond to the interpretive crisis of digital artifacts in museum exhibitions, and advance museums toward a new identity as interpreters of information civilization.

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.

Generative artificial intelligence is reshaping the production of academic texts. Conventional plagiarism detection based on textual similarity is increasingly insufficient for identifying AI-generated texts with original expressions. In Chinese academic contexts, the key issue is not merely whether a text can be classified as machine-generated, but how uncertain detection signals can be transformed into interpretable and reviewable risk clues for human academic review. Taking the ScholarGuard platform as a case, this study develops a multi-source evidence fusion framework for Chinese academic text detection by integrating perplexity perturbation, statistical features, and BERT-based semantic discrimination. The detection results are represented through RiskScore, risk levels, and paragraph-level prompts. Based on an exploratory test set of 120 Chinese academic texts covering law, political science, economics, and sociology, the study evaluates the system in terms of overall performance, disciplinary differences, baseline comparison, and ablation results. Under controlled test conditions, ScholarGuard achieves an accuracy of 82.5%, a precision of 86.3%, a recall of 78.3%, an F1 score of 82.1%, and an AUROC of 0.89. The results suggest that multi-source evidence fusion can improve the stability of AI-generated text risk identification in Chinese academic contexts. However, detection results should not be used as an automatic basis for assigning responsibility. AI-generated text detection is more appropriately positioned as a risk-indication tool in academic information quality governance, supporting source transparency, human verification, editorial review, and academic integrity management.

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.

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.

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.

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.

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.

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.

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.

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 such as 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.

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 August 1974, Chinese government launched a key project – "Information Processing System for Chinese Characters (also known as "Project 748"). "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.

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 will be analyzed for both achievements and problems. Clarify the current situation of the development prospects, practical status, and implementation obstacles of AI technology in university libraries, and propose practical suggestions to promote the development of AI technology in university libraries from three aspects: library leaders, librarians, and internal and external cooperation.

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 field of public cultural services. 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 article points out the important role of GLAMS in the age of digital intelligence, including the preservation, dissemination and utilisation of cultural heritage resources, as well as the exploration of ultimate human problems.

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.

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.