10 papers
Onsager-Machlup Posterior Transport for Deep Gaussian Processes
Jian Xu, Delu Zeng, John Paisley +1
Approximate inference over inducing variables is the central computational bottleneck of Deep Gaussian Processes (DGPs). Existing methods either fit an explicit density $q_Ï(\bU)$…
HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
Xianjie Liu, Yiman Hu, Yixiong Zou +3
Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding tasks. However, their performance on high-resolution images remains suboptimal. While…
From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction
Bencheng Yan, Yuejie Lei, Zhiyuan Zeng +7
Despite massive investments in scale, deep models for click-through rate (CTR) prediction often exhibit rapidly diminishing returns -- a stark contrast to the {predictable scaling…
Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoning
Yukang Lin, Xiang Zhang, Shichang Jia +9
Creative image in advertising is the heart and soul of e-commerce platform. An eye-catching creative image can enhance the shopping experience for users, boosting income for advert…
LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots
Haoran Sun, Xinrui Song, Xinyu Zhang +7
The integration of advertising auction mechanisms into large language model (LLM)-based chatbots presents a significant opportunity for commercialization, yet poses unique challeng…
LLM-Auction: Generative Auction towards LLM-Native Advertising
Chujie Zhao, Qun Hu, Shiping Song +4
The commercialization of LLM applications is the next frontier in online advertising, with LLM-native advertising emerging as a promising paradigm by integrating ads into LLM-gener…