arXiv:2509.16002v1 Announce Type: cross Abstract: A fully quantum reinforcement learning framework is developed that integrates a quantum Markov decision process, dynamic circuit-based qubit reuse, and Grover’s algorithm for trajectory optimization. The framework encodes states, actions, rewards, and transitions entirely within…
arXiv:2509.15269v1 Announce Type: new Abstract: The process by which Large Language Models (LLMs) acquire complex capabilities during training remains a key open question in mechanistic interpretability. This project investigates whether these learning dynamics can be characterized through the lens of…
arXiv:2509.15275v1 Announce Type: new Abstract: The team formation and routing problem is a challenging optimization problem with several real-world applications in fields such as airport, healthcare, and maintenance operations. To solve this problem, exact solution methods based on column generation…
arXiv:2509.15266v1 Announce Type: new Abstract: Understanding the real-world effects of recreational drug use remains a critical challenge in public health and biomedical research, especially as traditional surveillance systems often underrepresent user experiences. In this study, we leverage social media (specifically…
arXiv:2509.15259v1 Announce Type: new Abstract: Deep learning-based EEG classification is crucial for the automated detection of neurological disorders, improving diagnostic accuracy and enabling early intervention. However, the low signal-to-noise ratio of EEG signals limits model performance, making feature selection (FS)…
arXiv:2509.15258v1 Announce Type: new Abstract: Generative Artificial Intelligence (GenAI) has made significant advancements in fields such as computer vision (CV) and natural language processing (NLP), demonstrating its capability to synthesize high-fidelity data and improve generalization. Recently, there has been growing…
arXiv:2508.15411v2 Announce Type: replace-cross Abstract: Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. However, GenAI faces several major challenges in developing reliable and efficient GenAI-empowered systems due to its unpredictability and inefficiency.…
arXiv:2509.15316v1 Announce Type: new Abstract: Printed Electronics (PE) provide a flexible, cost-efficient alternative to silicon for implementing machine learning (ML) circuits, but their large feature sizes limit classifier complexity. Leveraging PE’s low fabrication and NRE costs, designers can tailor hardware…
arXiv:2509.15926v1 Announce Type: cross Abstract: Automated Essay Scoring (AES) systems now reach near human agreement on some public benchmarks, yet real-world adoption, especially in high-stakes examinations, remains limited. A principal obstacle is that most models output a single score without…
arXiv:2509.15328v1 Announce Type: new Abstract: Orientation-rich images, such as fingerprints and textures, often exhibit coherent angular directional patterns that are challenging to model using standard generative approaches based on isotropic Euclidean diffusion. Motivated by the role of phase synchronization in…
