Chengqiang Lu
Head of AI Search Generation Algorithms at Xiaohongshu
Chengqiang Lu is currently Head of AI Search Generation Algorithms at Xiaohongshu. He received his Master’s degree from the University of Science and Technology of China. His main research areas include large model pre-training/post-training, Agents, RAG, and AI4Sci. He has previously worked at Tencent QLab, Alibaba Qwen Team, and Xiaohongshu Search, focusing on algorithm research and real-world applications. He has published dozens of papers in top conferences and journals such as NeurIPS, KDD, AAAI, and ACL, with around 6,000 citations on Google Scholar.
Topic
Deployment of LLMs in Xiaohongshu AI Search in the Agent Era
With the rise of AI Agent technologies, search systems are shifting from passive responses to active exploration, creating new opportunities for business growth. At the same time, reinforcement learning (RL) provides search systems with dynamic decision-making and long-term value optimization, enabling AI Agents to better understand and meet users’ deeper needs. This talk will first introduce the background and challenges of applying AI Agents in Xiaohongshu AI Search, followed by an overview of advances in reinforcement learning applications. Finally, using Xiaohongshu’s business scenarios as examples, it will focus on the core algorithms of reinforcement learning agents and discuss the challenges and practical implementations in large-scale sparse-reward environments.
