Oct 2026· Scientific Journal of Reflection· 0 citations· 19 references
Financial Literacy and Behavior
Abstract
Digital transformation has strengthened the role of Accounting Information Systems (AIS) as a means of processing financial data that is fast, integrated, and technology-based. On the other hand, technological developments have also increased the complexity of fraud risks, necessitating more effective control systems. This study aims to explore accounting students’ perceptions of the role of AIS in fraud prevention in the digital age. The study employs a descriptive qualitative approach, with data collected through in-depth interviews with students who have taken courses in Accounting Information Systems, Auditing, and Internal Control. The data were analyzed through the stages of reduction, presentation, and drawing conclusions. The results indicate that students view AIS as a crucial tool in fraud prevention by enhancing transparency, recording accuracy, data security, and providing audit trails that facilitate transaction tracing. The use of technologies such as automation, big data, and artificial intelligence is also considered capable of supporting the early detection of fraud. However, the effectiveness of AIS remains dependent on the competence of human resources, individual integrity, and the quality of an organization’s internal controls. This study is expected to provide input for the development of accounting education and to enhance the readiness of prospective accountants to face organizational governance challenges in the digital age.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.