19 papers
GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks
Yejing Wang, Shengyu Zhou, Jinyu Lu +9
Generative recommendations (GR), which usually include item tokenizers and generative Large Language Models (LLMs), have demonstrated remarkable success across a wide range of scen…
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…
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…
Co-Diffusion: An Affinity-Aware Two-Stage Latent Diffusion Framework for Generalizable Drug-Target Affinity Prediction
Yining Qian, Pengjie Wang, Yixiao Li +4
Predicting drug-target affinity is fundamental to virtual screening and lead optimization. However, existing deep models often suffer from representation collapse in stringent cold…
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…