6 papers
AGPO: Asymmetric Group Policy Optimization for Verifiable Reasoning and Search Ads Relevance at JD
Yang Xu, Kun Yao, Yiming Deng +3
Reinforcement Learning with Verifiable Rewards (RLVR) has demonstrated notable success in enhancing the reasoning performance of large language models (LLMs). However, recent studi…
ADORE: Autonomous Domain-Oriented Relevance Engine for E-commerce
Zheng Fang, Donghao Xie, Ming Pang +5
Relevance modeling in e-commerce search remains challenged by semantic gaps in term-matching methods (e.g., BM25) and neural models' reliance on the scarcity of domain-specific har…
Generative Modeling with Multi-Instance Reward Learning for E-commerce Creative Optimization
Qiaolei Gu, Yu Li, DingYi Zeng +6
In e-commerce advertising, selecting the most compelling combination of creative elements -- such as titles, images, and highlights -- is critical for capturing user attention and…
Generative Retrieval and Alignment Model: A New Paradigm for E-commerce Retrieval
Ming Pang, Chunyuan Yuan, Xiaoyu He +8
Traditional sparse and dense retrieval methods struggle to leverage general world knowledge and often fail to capture the nuanced features of queries and products. With the advent…
A Semi-supervised Scalable Unified Framework for E-commerce Query Classification
Chunyuan Yuan, Chong Zhang, Zheng Fang +5
Query classification, including multiple subtasks such as intent and category prediction, is vital to e-commerce applications. E-commerce queries are usually short and lack context…
Multi-objective Aligned Bidword Generation Model for E-commerce Search Advertising
Zhenhui Liu, Chunyuan Yuan, Ming Pang +7
Retrieval systems primarily address the challenge of matching user queries with the most relevant advertisements, playing a crucial role in e-commerce search advertising. The diver…