3 citations · 5 across the 17 of their papers we have counts for
7 papers · 1 filter
Learning Deployable Causal Action Geometry under Temporal Non-Stationarity
Changjian Liu, Tianyu Wang, Yuwei Xu +6
Learning a response law for continuous decisions from observational time series is central to many real-world decision systems, yet temporal non-stationarity poses a fundamental ch…
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…
Multi-channel Uplift Policy Learning
Changjian Liu, Tianyu Wang, Xiaoxuan Deng +7
E-commerce platforms must allocate fixed marketing budgets across multiple channels to maximize business utility. However, standard predict-then-optimize (PTO) paradigms fail in th…
AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization
Yuejia Dou, Hesong Wang, Xinyu Zhang +6
Auto-bidding plays an essential role in online advertising, automatically adjusting bids for advertisers to optimize their commercial goals. The emerging AI-Generated Bidding (AIGB…
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…
DecisionLLM: Large Language Models for Long Sequence Decision Exploration
Xiaowei Lv, Zhilin Zhang, Yijun Li +10
Long-sequence decision-making, which is usually addressed through reinforcement learning (RL), is a critical component for optimizing strategic operations in dynamic environments,…