12 papers
Beyond Single Videos: Benchmarking and Active Evidence Seeking for E-Commerce Cross-Video Reasoning
Jinghan Zhao, Yiman Hu, Liang Wu +2
E-commerce videos are information-dense and frequently compared by consumers evaluating products and merchants assessing marketing strategies. However, existing multimodal models m…
PailitaoGR: Latent Think-with-Images for Generative Image Retrieval
Xiaomeng Fan, Yueran Liu, Shengyu Zhou +6
Generative retrieval has demonstrated strong performance by directly generating product semantic identifiers (SIDs). Extending this paradigm to image search, however, is nontrivial…
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 $q_ϕ(\bU)$…
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…
MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding
Junxian Wu, Chenghan Fu, Zhanheng Nie +6
With the rapid growth of e-commerce, exploring general representations rather than task-specific ones has attracted increasing attention. Although recent multimodal large language…
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…
MOON Embedding: Multimodal Representation Learning for E-commerce Search Advertising
Chenghan Fu, Daoze Zhang, Yukang Lin +8
We introduce MOON, our comprehensive set of sustainable iterative practices for multimodal representation learning for e-commerce applications. MOON has already been fully deployed…
MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding
Zhanheng Nie, Chenghan Fu, Daoze Zhang +5
Recent Multimodal Large Language Models (MLLMs) have significantly advanced e-commerce product understanding. However, they still face three challenges: (i) the modality imbalance…
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…
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…
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…
MOON: Generative MLLM-based Multimodal Representation Learning for E-commerce Product Understanding
Daoze Zhang, Chenghan Fu, Zhanheng Nie +7
With the rapid advancement of e-commerce, exploring general representations rather than task-specific ones has attracted increasing research attention. For product understanding, a…