activity
20212023
most citedWhen Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities

338 citations · 383 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2023

An Incremental Update Framework for Online Recommenders with Data-Driven Prior

Chen Yang, Jin Chen, Qian Yu +10

Online recommenders have attained growing interest and created great revenue for businesses. Given numerous users and items, incremental update becomes a mainstream paradigm for le…

cs.IR2023★ 338 cited

When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities

Jin Chen, Zheng Liu, Xu Huang +9

The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of…

cs.IR2022★ 8 cited

Cooperative Retriever and Ranker in Deep Recommenders

Xu Huang, Defu Lian, Jin Chen +3

Deep recommender systems (DRS) are intensively applied in modern web services. To deal with the massive web contents, DRS employs a two-stage workflow: retrieval and ranking, to ge…

cs.IR2022★ 4 cited

Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever

Jin Chen, Defu Lian, Yucheng Li +3

Recommender retrievers aim to rapidly retrieve a fraction of items from the entire item corpus when a user query requests, with the representative two-tower model trained with the…

cs.LG2021★ 20 cited

Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering

Jin Chen, Defu Lian, Binbin Jin +3

Variational AutoEncoder (VAE) has been extended as a representative nonlinear method for collaborative filtering. However, the bottleneck of VAE lies in the softmax computation ove…

cs.IR2021★ 1 cited

Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure

Jin Chen, Tiezheng Ge, Gangwei Jiang +3

Ad creatives are one of the prominent mediums for online e-commerce advertisements. Ad creatives with enjoyable visual appearance may increase the click-through rate (CTR) of produ…

cs.IR2021★ 12 cited

Automated Creative Optimization for E-Commerce Advertising

Jin Chen, Ju Xu, Gangwei Jiang +4

Advertising creatives are ubiquitous in E-commerce advertisements and aesthetic creatives may improve the click-through rate (CTR) of the products. Nowadays smart advertisement pla…