Web News Timeline Generation with Extended Task Prompting

The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time. This approach aids in discerning patterns and trends that might be obscured when news is viewed in isolation. By organizing news in a chronological sequence, it becomes easier to track the development of stories, understand the interrelation of events, and grasp the broader implications of news items. This is particularly helpful in sectors like finance and insurance, where timely understanding of the event development-ranging from extreme weather to political upheavals and health crises-is indispensable for effective risk management. While traditional natural language processing (NLP) techniques have had some success, they often fail to capture the news with nuanced relevance that are readily apparent to domain experts, hindering broader industry integration. The advance of Large Language Models (LLMs) offers a renewed opportunity to tackle this challenge. However, direct prompting LLMs for this task is often ineffective. Our study investigates the application of an extended task prompting technique to assess past news relevance. We demonstrate that enhancing conventional prompts with additional tasks boosts their effectiveness on various news dataset, rendering news timeline generation practical for professional use. This work has been deployed as a publicly accessible browser extension which is adopted within our network.

Flexible single multimode fiber imaging using white LED

Multimode fiber (MMF) has been proven to have good potential in imaging and optical communication because of its advantages of small diameter and large mode numbers. However, due to the mode coupling and modal dispersion, it is very sensitive to environmental changes. Minor changes in the fiber shape can lead to difficulties in information reconstruction. Here, white LED and cascaded Unet are used to achieve MMF imaging to eliminate the effect of fiber perturbations. The output speckle patterns in three different color channels of the CCD camera produced by transferring images through the MMF are concatenated and inputted into the cascaded Unet using channel stitching technology to improve the reconstruction effects. The average Pearson correlation coefficient (PCC) of the reconstructed images from the Fashion-MINIST dataset is 0.83. In order to check the flexibility of such a system, perturbation tests on the image reconstruction capability by changing the fiber shapes are conducted. The experimental results show that the MMF imaging system has good robustness properties, i. e. the average PCC remains 0.83 even after completely changing the shape of the MMF. This research potentially provides a flexible approach for the practical application of MMF imaging.