Vision-Language Models (VLMs) have significantly expanded AI’s ability to process multimodal information, yet they face persistent challenges. Proprietary models such as GPT-4V and Gemini-1.5-Pro achieve remarkable performance but lack transparency, limiting their adaptability. Open-source alternatives often struggle to match these models due to constraints in data diversity, training methodologies, and computational resources. Additionally, limited documentation… →
CONCLUSION: According to best trial practices, we report our statistical analysis plan and data management plan prior to locking the database and initiating the analyses. We anticipate that this practice will prevent analysis bias and improve the utility of the study’s reported results. →
Reinforcement learning (RL) trains agents to make sequential decisions by maximizing cumulative rewards. It has diverse applications, including robotics, gaming, and automation, where agents interact with environments to learn optimal behaviors. Traditional RL methods fall into two categories: model-free and model-based approaches. Model-free techniques prioritize simplicity but require extensive training data, while model-based methods introduce… →
CONCLUSION: Our data indicate no statistical evidence that minimally invasive surgery is associated with poorer clinical outcomes for patients meeting the SHAPE criteria who underwent simple hysterectomy. Because the surgical approach was not a randomization factor, a large prospective trial is needed to confirm our results before a routine simple hysterectomy by minimally invasive surgery… →
Large Language Models (LLMs) have emerged as transformative tools in research and industry, with their performance directly correlating to model size. However, training these massive models presents significant challenges, related to computational resources, time, and cost. The training process for state-of-the-art models like Llama 3 405B requires extensive hardware infrastructure, utilizing up to 16,000 H100… →
LLMs based on transformer architectures, such as GPT and LLaMA series, have excelled in NLP tasks due to their extensive parameterization and large training datasets. However, research indicates that not all learned parameters are necessary to retain performance, prompting the development of post-training compression techniques to enhance efficiency without significantly reducing inference quality. For example,… →
CONCLUSION: Emphasising nonconformity with mental health stereotypes, portraying positive aspects and utilising short video formats on social media platforms can potentially reduce stigma in the short term. Long-term effectiveness and identification of specific factors optimising attitudes towards mental health help-seeking warrant further investigation. →
Computer Vision is at the intersection of innovation and practicality, allowing machines to interpret and process visual data in ways that were once considered purely science fiction. From enabling autonomous vehicles to enhancing healthcare diagnostics, Computer Vision Engineers are at the forefront of technological advancements shaping the future. With the explosive growth of artificial intelligence… →