3 citations · 9 across the 13 of their papers we have counts for
14 papers
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…
BOFA: Bridge-Layer Orthogonal Low-Rank Fusion for CLIP-Based Class-Incremental Learning
Lan Li, Tao Hu, Da-Wei Zhou +3
Class-Incremental Learning (CIL) aims to continually learn new categories without forgetting previously acquired knowledge. Vision-language models such as CLIP offer strong transfe…
Make It Long, Keep It Fast: End-to-End 10K Long User Behavior Sequence Modeling for Billion-Scale Douyin Recommendation
Lin Guan, Jia-Qi Yang, Zhishan Zhao +12
Short-video recommenders such as Douyin must exploit extremely long user behavior histories without breaking latency or cost budgets. We present an end-to-end industrial recommende…
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…
Physics-informed Inverse Design of Multi-bit Programmable Metasurfaces
Yucheng Xu, Jia-Qi Yang, Kebin Fan +8
Emerging reconfigurable metasurfaces offer various possibilities in programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing g…
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…
COURIER: Contrastive User Intention Reconstruction for Large-Scale Visual Recommendation
Jia-Qi Yang, Chenglei Dai, Dan OU +5
With the advancement of multimedia internet, the impact of visual characteristics on the decision of users to click or not within the online retail industry is increasingly signifi…
Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping
Jia-Qi Yang, De-Chuan Zhan, Le Gan
Research has shown that deep networks tend to be overly optimistic about their predictions, leading to an underestimation of prediction errors. Due to the limited nature of data, e…
IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics
Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen +3
Aiding humans with scientific designs is one of the most exciting of artificial intelligence (AI) and machine learning (ML), due to their potential for the discovery of new drugs,…
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…
RID-Noise: Towards Robust Inverse Design under Noisy Environments
Jia-Qi Yang, Ke-Bin Fan, Hao Ma +1
From an engineering perspective, a design should not only perform well in an ideal condition, but should also resist noises. Such a design methodology, namely robust design, has be…
Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling
Jia-Qi Yang, Xiang Li, Shuguang Han +4
Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner t…