Regulatory non-compliance, fragmented traceability, and counterfeit drugs are ongoing problems for the pharmaceutical supply chain. To close these gaps, blockchain technology provides a transparent, tamper-proof, and decentralised platform that makes it possible for safe data sharing, automated compliance, and real-time tracking. This chapter looks at how blockchain’s immutable audit trails, smart contracts, and IoT integration improve drug integrity. It highlights enhanced recall efficiency, decreased fraud, and reinforced adherence to Good Distribution Practices (GDP) by referencing case studies such as MediLedger (U.S.) and PharmaLedger (EU). In order to contextualise blockchain’s value in protecting public health, it also examines international instances of counterfeit drugs from Colombia, the United States, and India. This chapter concludes by outlining future trends in which blockchain, artificial intelligence, and Internet of Things become a fundamental component of pharmaceutical governance and addressing adoption challenges, including scalability, integration with legacy systems, and regulatory fragmentation.
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...
