ChinaRxiv · Open Access in English
Translated papers from the Chinese Preprint site, Chinaxiv
136 accessible records Original PDFs retained
Showing 50 of 136 papers in AI / CS
**[Purpose/Significance]** Driven by the wave of digitalization, the explosion of network information and the proliferation of recommendation algorithms have jointly given rise to the "information cocoon" phenomenon. This restricts the breadth of public information acquisition and the depth of cultu…
With the development of financial technology, fintech courses in universities face challenges such as an overemphasis on theory, insufficient practical application, and limited teaching tools, making it difficult for students to master end-to-end investment research operational capabilities. This pa…
Cryptography is the cornerstone of trusted computing. Currently, classical cryptographic systems are facing severe challenges from quantum computing. While post-quantum cryptography (PQC) can resist known quantum attacks, with the continuous development and maturation of quantum computing, the emerg…
In large-scale Internet of Things (IoT) deployments, terminal nodes are often constrained by factors such as power consumption, cost, and installation location, preventing them from accessing the Internet directly and forcing them to rely on nearby devices to forward data. If the forwarding path lac…
The advent of large language models represents a new revolution in information technology, and their application will bring new vitality to various industries. This paper focuses on the application of large models in the maritime field, proposing the application prospects as well as the risks and ch…
This study aims to construct a unified, systematic, and referable knowledge framework for the annotation of art image datasets, addressing the issues of ambiguous definitions and inconsistent results caused by the lack of common standards during the annotation process. To achieve this goal, based on…
The "Communiqué of the Fourth Plenary Session of the 20th Central Committee of the Communist Party of China" mentions high-quality development 10 times, particularly emphasizing that economic and social development during the "15th Five-Year Plan" period should "take the promotion of high-quality de…
In the study of beam dynamics for high-intensity linear accelerators, 3D multi-particle simulations based on the particle-in-cell (PIC) algorithm are necessary due to numerous nonlinear effects caused by strong space charge effects. However, since such simulations require a large amount of computati…
Space objects in Geostationary Earth Orbit (GEO) present significant detection challenges in optical imaging due to weak signals, complex stellar backgrounds, and environmental interference. In this paper, we enhance high-frequency features of GEO targets while suppressing background noise at the si…
This paper examines the fundamental concepts of the metaverse and industrial metaverse, along with the characteristics of their key enabling technologies, and argues that the industrial metaverse represents a new stage in the digitalization and intelligentization of industry and the broader industri…
Format-Preserving Encryption (FPE) has wide applications in sensitive data privacy protection; however, existing standard algorithms struggle to resist slide correlation and linear cryptanalysis attacks, and their algorithmic efficiency is relatively low. This paper proposes a Finite-Radix Format-Pr…
We point out that neural networks are not black boxes, and their generalization stems from the ability to dynamically map a dataset to the extrema of the model function. We further prove that the number of extrema in a neural network is positively correlated with the number of its parameters. We the…
[Purpose] The low-altitude economy constitutes a strategic frontier leading the new round of global industrial transformation. This study aims to deeply decode the strategic intent, internal structure, and functional effectiveness of U.S. low-altitude economy policies, providing intelligence support…
Consciousness is considered the most challenging problem in the science of the mind, especially Chalmers' hard problem. From the standpoint of systems science philosophy, many consciousness theories overlook the structure-function correlation principle, thereby reducing their explanatory power regar…
## Abstract Currently, global cultural competition is becoming increasingly intense. Domestic cultural products face difficulties in "breaking out of the circle," and their "overseas expansion" to gain followers is further challenged by issues such as a lack of local adaptation and cultural discount…
Systematically excavating strategies with long-term evolutionary advantages in multi-agent systems constitutes a pivotal challenge in evolutionary game theory, complex systems science, and artificial intelligence research. This paper proposes and implements a unified strategy search framework—AI4Gam…
Abstract: [Objective] To investigate the pathways and mechanisms through which AIGC technology drives the digital dissemination of intangible cultural heritage (ICH) to resolve its inheritance predicament. [Methods] Grounded in a technology adaptation perspective, this study employs literature resea…
[Objective] To address the "technical silo" issue in the full drug discovery and development pipeline, where target screening, molecular design, efficacy evaluation, and clinical translation rely on isolated models and lack a lightweight end-to-end integrated framework. [Methods] Based on the AutoGe…
Safety early warning and optimal dispatching of hydropower systems rely on efficient analysis of long-term high-precision time-series monitoring data (such as minute-level dam water levels, inflow rates, etc.). However, existing monitoring modes still primarily rely on manual retrieval, suffering fr…
Brain-computer interfaces (BCIs) establish direct communication channels between the human brain and external devices, enabling not only novel human-computer interaction paradigms but also providing an important technological foundation for innovative clinical treatments. BCI decoding methods can be…
## Abstract **[Purpose/Significance]** The introduction of digital twin technology into digital museum applications has imposed new requirements on the content organization and service formats of exhibit services. Researching digital twin models oriented toward museum exhibit services can provide a …
[Abstract] This study proposes a method for constructing a prosodic lexicon for Lhasa Tibetan based on a continuous speech database, applicable to low-resource and complex languages. The prosodic lexicon constructed from a small set of high-quality data (3.77 hours, 2,526 sentences) significantly im…
Named Entity Recognition (NER, NamedEntityRecognition) is a critical component in natural language processing systems, widely applied in tasks such as question answering, information retrieval, and relation extraction. Although NER systems have undergone decades of research and development, named en…
This paper comprehensively surveys the evolutionary trajectory, technical principles, market applications, development trends, and challenges confronting reconfigurable chip technology. With the rapid advancement of information technology, emerging technologies have imposed increasingly stringent de…
Advances in technology and the development of the Internet have enabled the storage and distribution of large-scale unstructured data (such as audio, video, and natural language text). However, any such storage and distribution incurs certain costs, naturally prompting considerations for the efficie…
Fractal image decoding has been effectively accelerated by using the range-averaged image (RAI) as the initial image in decoding process, and only one iteration is needed to obtain the decoded image quality with acceptable quality. To further improve the decoded image quality while maintaining real-…
We point out that neural networks are not black boxes, and their generalization stems from the ability to dynamically map a dataset to the local extrema of the model function. We further prove that the number of local extrema in a neural network is positively correlated with the number of its parame…
This study proposes and validates a novel psycho-judicial attack paradigm termed "Cognitive Trial." Unlike traditional prompt injection, this paradigm is completed through a multi-stage game, exploiting core architectural vulnerabilities in Large Language Models (LLMs) that arise from their pursuit …
Investigating the influencing factors of emergency information acquisition among rural left-behind children during major public health events can provide valuable recommendations for improving their emergency information acquisition capabilities. This study conducted interviews with 34 rural left-be…
The phenomenon of citizens sharing unverified information on social media can, to a certain extent, reflect the level of information literacy education in a region. This study aims to investigate the attitudes and behaviors of the general public in Taiwan, China toward unverified information on soci…
Micro-expressions refer to brief facial actions that individuals unconsciously display when attempting to suppress genuine emotions. Owing to their non-invasive nature, they possess significant application value in domains such as national security and public security. To address challenges includin…
We present a new method for structural sequence analysis grounded in Algorithmic Information Theory (AIT). At its core is the Ladderpath approach, which extracts nested and hierarchical relationships among repeated substructures in linguistic sequences---an instantiation of AIT’s principle of descri…
Mathematical reasoning presents a significant challenge for Large Language Models (LLMs) as it requires ensuring the correctness of each reasoning step. Researchers have been strengthening the mathematical reasoning abilities of LLMs through supervised fine-tuning, but due to the inability to suppre…
[Purpose/Significance] This study explores the adaptability and evolution path of Agent technology in scientific and technological intelligence work, addressing the increasingly growing demands for intelligence and cognition in intelligence operations. [Method/Process] Based on the functional evolut…
Natural language is considered closely intertwined with human cognition, with linguistic structures posited to offer profound insights into the cognitive system. However, as a coding system, natural language encodes diverse objects into unified forms; its prominent formal features capture people’s a…
With the rapid penetration of artificial intelligence across multiple industries and scenarios, integrating the language understanding advantages of general large models with industry-specific knowledge bases in complex real-world applications has become a key challenge in constructing next-generati…
Objective: With the development of internet big data and machine learning methods, an increasing number of studies combine text analysis and machine learning to predict satisfaction. In research on building life satisfaction prediction models, to address the challenge of obtaining large amounts of e…
This paper analyzes the major challenges currently facing Large Language Models (LLMs) and proposes concrete solutions. It identifies that the representation and computation of probabilistic conceptual structure models is crucial, provides a brief overview of the related technology—Deep Semantic Mod…
OpenAI's Generative Pre-trained Transformer 4 (GPT-4) is a powerful large language model with a certain degree of intelligence in understanding and generating coherent text. We are exploring whether GPT-4 is capable of acting as a die, i.e. generating random numbers. We show that GPT-4 does not appe…
To promote critical improvement of systems related to "external regulations for research integrity" both within and beyond the scientific community, this study examines the practical drivers and theoretical logic underlying the institutional practice of "random inspection of national science and tec…
[Objective] Analyze the definition and properties of information capacity based on the information sextuple model, propose formulas relating information to matter, energy, and time, and provide theoretical reference for information science, particularly for applications in quantum information techno…
Until now, image quality assessment has not addressed color issues. The literature on image quality assessment primarily evaluates the degree of degradation (deterioration) of image quality during image processing procedures such as compression and transmission. A planar image is essentially a two-d…
[Purpose] Large scientific facilities play a crucial role in promoting the output of major scientific and technological achievements, and their clustered development and collaborative innovation effects continuously lead regional industrial innovation and development. To enable large facilities to b…
To address issues such as low registration efficiency and large errors in the registration of two partially overlapping point clouds, we propose a point cloud registration algorithm based on mixed features sampled from the overlapping region. First, we predict the overlap score for each point throug…
Bone age assessment is a commonly used method for detecting endocrine and growth abnormalities in children; however, low-quality hand X-ray images in deep learning methods reduce the final assessment accuracy. To address this issue, we propose an alignment network that increases the region of intere…
Employing reinforcement learning to address robot manipulation problems offers numerous advantages; however, traditional reinforcement learning algorithms encounter challenges associated with sparse rewards, and the policies obtained are difficult to directly deploy in real-world environments. To en…
To address the problems of ambiguous boundaries between high-value and low-value parts and unreasonable disassembly depth of waste products, a multi-objective disassembly scheme decision-making method for products considering functional degradation of parts is proposed. The influence of specific par…
In recent years, the application of unmanned aerial vehicles (UAVs) has become increasingly widespread, and the coordination of multiple UAVs to accomplish tasks has substantially improved operational efficiency. Motivated by this phenomenon, numerous scholars have devoted themselves to research on …
To resist quantum algorithm attacks and address the vulnerability where malicious signers exploit the complete anonymity of ring signature technology to output multiple signatures for double-spending attacks, while simultaneously solving the problem of unnecessary system overhead waste, a novel latt…
To address the issues of high latency in existing low-orbit satellite network authentication schemes that utilize centralized authentication methods and significant computational overhead arising from complex bilinear mappings, we introduce a certificateless authentication model and propose an effic…
