Worth Multiple Word

Research on "worth" in various contexts focuses on quantifying and predicting value across diverse data types, from academic articles and videos to images and time series. Current efforts leverage large language models (LLMs) and diffusion models to extract semantic features and predict impact based on textual and visual content, employing techniques like text embedding alignment and multi-attribute inversion. These advancements improve efficiency in tasks such as information retrieval, video captioning, and image generation, while also offering insights into model interpretability and robustness. The overall impact lies in developing more efficient and effective methods for analyzing and generating data across multiple modalities, with applications ranging from academic impact assessment to improved AI model training.