Understanding and processing human language has always been a difficult challenge in artificial intelligence. Early AI systems often struggled to handle tasks like translating languages, generating meaningful text, or answering questions accurately. These systems relied on rigid rules or basic statistical methods that couldn’t capture the nuances of context, grammar, or cultural meaning. As a… →
Large Language Models (LLMs) have shown remarkable capabilities across diverse natural language processing tasks, from generating text to contextual reasoning. However, their efficiency is often hampered by the quadratic complexity of the self-attention mechanism. This challenge becomes particularly pronounced with longer input sequences, where computational and memory demands grow significantly. Traditional methods that modify self-attention… →
Multi-hop queries have always given LLM agents a hard time with their solutions, necessitating multiple reasoning steps and information from different sources. They are crucial for analyzing a model’s comprehension, reasoning, and function-calling capabilities. At this time when new large models are booming every other day with claims of unparalleled capabilities, multi-hop tools realistically assess… →
The rise of multimodal applications has highlighted the importance of instruction data in training MLMs to handle complex image-based queries effectively. Current practices for generating such data rely on LLMs or MLMs, which, despite their effectiveness, face several challenges. These include high costs, licensing restrictions, and susceptibility to hallucinations—generating inaccurate or unreliable content. Additionally, the… →
CONCLUSION: The LOCATE model shows potential for impact, particularly in reducing waiting times for patients at high risk of developing severe liver disease due to NAFLD. A larger sample and longer follow-ups are needed to measure additional clinical outcomes. →
CONCLUSION: By adopting a heart-rate dependent and free-breathing protocol, the contrast medium volume were reduced in coronary CTA for patients with COPD, while the image quality was remained comparable to those acquired with routine CTA protocol. →
CONCLUSION: In this study breathing exercises could reduce fatigue and dyspnea, and improve NYHA functional classification of HF patients which can be included in nursing care plans for respiratory rehabilitation in HF. →
To assess the efficacy and safety of LiWei Capsule (LWC) in the treatment of chronic non-atrophic gastritis (CNG) with erosions and damp-heat stasis syndrome, based on Traditional Chinese Medicine (TCM) principles. This phase II, multicenter, randomized, double-blind, placebo- and positive-controlled trial enrolled patients diagnosed with CNG with erosions and damp-heat stasis syndrome. Participants were allocated… →
CONCLUSIONS: Results from this investigation support the feasibility of the BfitBwell Telehealth Program and a subsequent efficacy trial. Novel program components also provide potential models for improving exercise program efficacy and efficiency through asynchronous exercise prescription and symptom monitoring. →
Artificial General Intelligence (AGI) seeks to create systems that can perform various tasks, reasoning, and learning with human-like adaptability. Unlike narrow AI, AGI aspires to generalize its capabilities across multiple domains, enabling machines to operate in dynamic and unpredictable environments. Achieving this requires combining sensory perception, abstract reasoning, and decision-making with a robust memory and… →