4/5/2024 0 Comments Learn robotc languageThis approach allows the visual language model to discern the different levels of information in a prompt, ranging from specific details to broader categories and overarching themes across multiple knowledge domains, as shown in Figure 3. Listen now Opens in a new tab How to model structural knowledgeĪfter identifying and structuring the relationships within the generated prompt descriptions, we implement Hierarchical Prompt Tuning (HTP), a new prompt-tuning framework that organizes content hierarchically. With instructions fed into the LLM, we can receive category-related descriptions along with corresponding structured graphs. For example, when defining “water lily,” we include entities like “leaves” or “blooms”, their attributes, “round” and “white”, and then apply LLMs’ reasoning capabilities to identify how these terms relate to each other. This is shown in Figure 2. These graphs contain structured information, with entities (objects, people, and concepts), attributes (characteristics), and the relationships between them. A structured graph provides descriptions for each class name.įigure 1 illustrates our method for constructing a structured graph containing key details for each category, or class. By creating detailed graphs of image descriptions, we leverage LLMs’ linguistic knowledge to produce richer images, expanding their utility in practical applications. In our paper, “ Learning Hierarchical Prompt with Structured Linguistic Knowledge for Language Models,” presented at AAAI-24, we introduce a novel approach using large language models (LLMs) to enhance the images created by visual language models. However, creating high-quality visuals requires crafting precise prompts that capture the relationships among the different image elements, a capability that standard prompts lack. We’re seeing remarkable abilities from visual language models in transforming text descriptions into images. This research paper was presented at the 38th Annual AAAI Conference on Artificial Intelligence (opens in new tab) (AAAI-24), the premier forum for advancing understanding of intelligence and its implementation in machines.
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