Instruction-based image editing improves the controllability and flexibility of image manipulation via natural commands without elaborate descriptions or regional masks. However, human instructions are sometimes too brief for current methods to capture and follow. Multimodal large language models (MLLMs) show promising capabilities in cross-modal understanding and visual-aware response generation via LMs. We investigate how MLLMs… →
Large Language Models (LLMs) with billions of parameters have drastically transformed AI applications. However, their demanding computation during inference has raised significant challenges for deployment on resource-constrained devices. Despite recent trends favoring alternative activation functions such as GELU or SiLU, known for increased computation, this study strongly advocates for reinstating ReLU activation in LLMs. We… →
Rendering scenes observed in a monocular video from novel viewpoints is a chal- lenging problem. For static scenes the community has studied both scene-specific optimization techniques, which optimize on every test scene, and generalized tech- niques, which only run a deep net forward pass on a test scene. In contrast, for dy- namic scenes, scene-specific… →
There has been rapid growth in the open-source landscape for Large Language Models (LLMs) after the release of the Llama3 model and its successor, Llama 2, by Meta in 2023. This release has led to the development of multiple innovative LLMs. These models have played an important role in this dynamic field by influencing natural… →
Language models are incredibly powerful tools that can understand and generate human-like text by learning patterns from massive datasets. However, the traditional method of training these models, called “next-token prediction,” has its limitations. It essentially teaches the model to predict the next word in a sequence, but this approach can lead to suboptimal performance, especially… →
Natural Language Processing (NLP) is integral to artificial intelligence, enabling seamless communication between humans and computers. This interdisciplinary field incorporates linguistics, computer science, and mathematics, facilitating automatic translation, text categorization, and sentiment analysis. Traditional NLP methods like CNN, RNN, and LSTM have evolved with transformer architecture and large language models (LLMs) like GPT and BERT… →
CONCLUSIONS: The 1 × 30 min protocol produced equivalent color change to the other bleaching protocols with reduced risk of TS and shorter application time. →
This parallel-arm, phase I study investigated the potential cytochrome P450 (CYP)3A induction effect of NBI-1065845 (TAK-653), an investigational α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor potentiator in phase II development for major depressive disorder. The midazolam treatment arm received the sensitive CYP3A substrate midazolam on Day 1, followed by NBI-1065845 alone on Days 5-13; on Day 14, NBI-1065845 was… →
Artificial intelligence (AI) in medicine is revolutionizing how clinicians handle complex tasks such as diagnosing patients, planning treatments, and staying current with the latest research. Advanced AI models promise to enhance healthcare by increasing accuracy and efficiency. The vast array of medical data, such as images, videos, and electronic health records (EHRs), challenges AI models… →
GitHub Copilot GitHub Copilot stands as a market-leading AI-powered coding assistant. Engineered to enable developers to produce superior code with greater efficiency, Copilot operates on the foundation of OpenAI’s Codex language model. This model is trained on both natural language and a broad database of public code, allowing it to offer insightful suggestions. From completing… →