Formal mathematical reasoning represents a significant frontier in artificial intelligence, addressing fundamental logic, computation, and problem-solving challenges. This field focuses on enabling machines to handle abstract mathematical reasoning with precision and rigor, extending AI’s applications in science, engineering, and other quantitative domains. Unlike natural language processing or vision-based AI, this area uniquely combines structured logic… →
CONCLUSIONS: Recruitment of people with stroke/TIA to a trial comparing a BP self-monitoring and digital behavioural intervention to usual care was feasible prior to the COVID-19 pandemic and the vast majority of those randomised to intervention used it while the trial was running. Routinely recorded blood pressure control improved in both groups. Digital interventions including… →
Colonoscopy is a valuable tool for colorectal cancer screening and health checkups, with increasing utilization annually. Assisted entry is a standard procedure during electronic colonoscopy. In China, most clinically assisted colonoscopy procedures involve a nurse directly applying abdominal pressure to the patient’s abdomen. This maneuver provides a fulcrum for the physician performing the procedure, facilitating… →
This research evaluated the effectiveness of an online simulation-based serious game as a learning tool in diagnosis and treatment planning for oral lesions (SimOL) in comparison to a pre-recorded lecture-based approach and to determine its appropriate integration into the undergraduate dental curriculum. A crossover randomized control trial was conducted with a cohort of 77 dental… →
Social media platforms have revolutionized human interaction, creating dynamic environments where millions of users exchange information, form communities, and influence one another. These platforms, including X and Reddit, are not just tools for communication but have become critical ecosystems for understanding modern societal behaviors. Simulating such intricate interactions is vital for studying misinformation, group polarization,… →
In today’s world, Multimodal large language models (MLLMs) are advanced systems that process and understand multiple input forms, such as text and images. By interpreting these diverse inputs, they aim to reason through tasks and generate accurate outputs. However, MLLMs often fail at complex tasks because they lack structured processes to break problems into smaller… →
Large language models (LLMs) built using transformer architectures heavily depend on pre-training with large-scale data to predict sequential tokens. This complex and resource-intensive process requires enormous computational infrastructure and well-constructed data pipelines. The growing demand for efficient and accessible LLMs has led researchers to explore techniques that balance resource use and performance, emphasizing achieving competitive… →
Large language models (LLMs) encounter significant difficulties in performing efficient and logically consistent reasoning. Existing methods, such as CoT prompting, are extremely computationally intensive, not scalable, and unsuitable for real-time applications or limited resources. These limitations restrict their applicability in financial analysis and decision-making, which require speed and accuracy. State-of-the-art reasoning approaches, like CoT, build… →
Machine unlearning is driven by the need for data autonomy, allowing individuals to request the removal of their data’s influence on machine learning models. This field complements data privacy efforts, which focus on preventing models from revealing sensitive information about the training data through attacks like membership inference or reconstruction. While differential privacy methods limit… →
The semiconductor industry enables advancements in consumer electronics, automotive systems, and cutting-edge computing technologies. The production of semiconductors involves sophisticated processes that demand unparalleled precision and expertise. These processes include chip design, manufacturing, testing, and optimization, each stage requiring deep domain knowledge. The field has traditionally depended on seasoned engineers whose experience has been built… →