From the 1 of 9 papers with an AI index.
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TransX: Scaling Transformer-based Recommendation via Behavioral and Serving Stream Crossings
Da Xu, Liyan Fang, Divya Venugopalan +5
Modern industrial recommender systems (RecSys) increasingly adopt Transformer-based sequence models, with an emerging paradigm that frames recommendation as next-token prediction o…
Deep-learning Causal Retrieval Optimization for Efficient e-commerce Distribution in Pinterest
Junpeng Hou, XianXing Zhang, Sai Xiao +6
The paper presents a deep learning system that decides when to trigger shopping recommendations in Pinterest, using causal inference to reduce unnecessary triggers while maintainin…
A Unified Structured Query Understanding Framework for Industrial Semantic Search
Ping Liu, Qianqi Shen, Jianqiang Shen +15
Query understanding in large-scale industrial search systems is typically implemented as a cascade of disparate, task-specific components. While individually optimizable, this frag…
How Does Empowering Users with Greater System Control Affect News Filter Bubbles?
Ping Liu, Karthik Shivaram, Aron Culotta +2
While recommendation systems enable users to find articles of interest, they can also create ``filter bubbles'' by presenting content that reinforces users' pre-existing beliefs. U…
Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent
Zhentao Xu, Shangjin Zhang, Emir Poyraz +7
Large Language Model (LLM) agents are increasingly used in real-world products, where personalized and context-aware user interactions are essential. A central enabler of such capa…
Policy-Grounded Dynamic Facet Suggestions for Job Search
Dan Xu, Baofen Zheng, Qianqi Shen +11
Job seekers often initiate search with short, underspecified queries. At LinkedIn, over 80% of job-related queries contain three or fewer keywords, making accurate user intent infe…