Personalized search ranking systems are critical for driving engagement and revenue in modern e-commerce and short-video platforms. While existing methods excel at estimating users' broad interests based on the filtered historical behaviors, they typically under-exploit explicit alignment between a user's real-time intent (represented by the user query) and their past actions. In this paper, we propose DiffusionGS, a novel and scalable approach powered by generative models. Our key insight is that user queries can serve as explicit intent anchors to facilitate the extraction of users' immediate interests from long-term, noisy historical behaviors. Specifically, we formulate interest extraction as a conditional denoising task, where the user's query guides a conditional diffusion process to produce a robust, user intent-aware representation from their behavioral sequence. We propose the User-aware Denoising Layer (UDL) to incorporate user-specific profiles into the optimization of attention distribution on the user's past actions. By reframing queries as intent priors and leveraging diffusion-based denoising, our method provides a powerful mechanism for capturing dynamic user interest shifts. Extensive offline and online experiments demonstrate the superiority of DiffusionGS over state-of-the-art methods.

But Google's global search dominance makes it the most important player, and the company has already rolled out AI Overviews to more than a billion people worldwide. The result is searches that feel more like conversations. Google and OpenAI both report that people interact differently with generative search--they ask longer questions and pose more follow-ups. This new application of AI has serious implications for online advertising and (gulp) media. Because these search products often summarize information from online news stories and articles in their responses, concerns abound that generative search results will leave little reason for people to click through to the original sources, depriving those websites of potential ad revenue.

The race to bring more AI features to search is escalating, with Microsoft moving forward with additional tools for Bing. Today, the company began previews for Bing generative search, where the top result for a user's query will be an original response compiled by AI. The blog post about Bing generative search showed a few sample results. In addition to the overview statement, Microsoft will provide links to the main sources that the large-language models and small-language models used to create their answer. It will also have a section of related information.