The development of vision-language models (VLMs) has faced challenges in handling complex visual question-answering tasks. Despite substantial advances in reasoning capabilities by large language models like OpenAI’s GPT-o1, VLMs still struggle with systematic and structured reasoning. Current models often lack the ability to organize information and engage in logical, sequential reasoning, limiting their effectiveness for… →
CONCLUSION: This research identifies critical factors influencing relapse in individuals with SUDs and introduces a novel, non-pharmacological intervention that significantly diminishes relapse rates and enhances recovery outcomes. It highlights the importance of physical activity in promoting mental health improvement and integrates traditional Chinese exercises with contemporary psychological insights, offering a comprehensive approach to drug rehabilitation… →
In recent years, the development of large language models has significantly advanced natural language processing (NLP). These models, trained on extensive datasets, can generate, understand, and analyze human language with remarkable proficiency. However, building such models requires substantial amounts of data, and access to high-quality multilingual datasets remains a considerable challenge. The scarcity of openly… →
The field of artificial intelligence is advancing rapidly, yet significant challenges remain in developing and applying AI systems, particularly in complex reasoning. Many current AI solutions, including advanced models like GPT-4 and Claude 3.5 Sonnet, still struggle with intricate coding tasks, deep conversations, and mathematical reasoning. The limitations of individual models—no matter how sophisticated—lead to… →
Recommender systems have been widely applied for studying user preferences; however, they face significant challenges in accurately capturing user preferences, particularly in the context of neural graph collaborative filtering. While these systems use interaction histories between users and items through Graph Neural Networks (GNNs) to mine latent information and capture high-order interactions, the quality of… →
CONCLUSIONS: Differences among the RCTs may partially be explained by concomitant background therapy (methotrexate) in the RA trial, stable doses of azathioprine, 6-mercaptopurine or methotrexate in 36% of patients with CD and absence of background therapy in the PsO RCT. The analyses further confirm the biosimilarity of adalimumab-adbm with the adalimumab RP across IMIDs and… →
Identifying gene deletion strategies for growth-coupled production in genome-scale metabolic models presents significant computational challenges. Growth-coupled production, which links cell growth to the synthesis of target metabolites, is essential for metabolic engineering applications. However, deriving gene deletion strategies for large-scale models places high computational demand since there is a massive search space combined with the… →
In recent times, Retrieval-augmented generation (RAG) has become popular due to its ability to solve challenges using Large Language Models, such as hallucinations and outdated training data. A RAG pipeline consists of two components: a retriever and a reader. The retriever component finds useful information from an exterior knowledge base, which is then included alongside… →