Sep 2026· Journal of Intelligent Computing System· 0 citations
Abstract
Particularly in terms of supporting writing, artificial intelligence can now do much more. It alters children's reading and writing skills as well as teacher evaluation of their work. Apps that help with language, programs that offer quick feedback, and tools that generate text are all examples of AI that can provide helpful advice, rapid responses, and additional writing practice for students. These fresh technologies provide problems even if they are beneficial and help to save time. Problems with honesty in schoolwork, excessive reliance on computer applications, the equilibrium between appropriately utilizing technology and not, and the loss of critical thinking or creativity comprise these. These obstacles are forcing teachers to reevaluate their teaching methods and ensure AI supports student learning instead of merely dominating. Although AI in education has some limitations and challenges, its potential to be enormously beneficial in the classroom is also quite high. This piece discusses more on how these difficulties come up while teaching writing. The report demands explicit instructions, suitable teacher training, and substantial school support to effectively apply artificial intelligence in order to enhance education.
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
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...
This work revisits schema linking when using the latest generation of large language models (LLMs) and finds empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz et al.· arXiv.org· 109 citations· ⚡19
A novel threat is unveiled in which attackers steer the RAG system's response by injecting malicious passages into its knowledge base, enabling the attacker to steer the response without altering the user input or modifying the RAG weights.
Jiaqi Xue, Meng Zheng, Yebowen Hu et al.· arXiv.org· 109 citations· ⚡8
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