3 citations · 9 across the 13 of their papers we have counts for
6 papers · 1 filter
SequenceO1: End-to-End Ultra-Long (100K) Sequence Modeling in Recommendation with Low-Rank Caching
Lin Guan, Jia-Qi Yang, Zhishan Zhao +15
Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking models operate under strict latenc…
Revisiting Content-Based Music Recommendation: Efficient Feature Aggregation from Large-Scale Music Models
Yizhi Zhou, Jia-Qi Yang, De-Chuan Zhan +1
Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking stages, predominantly rely on…
Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens
Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen +3
Characterizing users and items through vector representations is crucial for various tasks in recommender systems. Recent approaches attempt to apply Large Language Models (LLMs) i…
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer
Zhihao Guan, Jia-Qi Yang, Yang Yang +3
Job recommendation aims to provide potential talents with suitable job descriptions (JDs) consistent with their career trajectory, which plays an essential role in proactive talent…
RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction
Song-Li Wu, Liang Du, Jia-Qi Yang +4
Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user. Most recent cutting-edge methods…
Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems
Jia-Qi Yang, De-Chuan Zhan
Predicting conversion rate (e.g., the probability that a user will purchase an item) is a fundamental problem in machine learning based recommender systems. However, accurate conve…