15 citations · 30 across the 8 of their papers we have counts for
4 papers · 1 filter
Multi-modal Relational Item Representation Learning for Inferring Substitutable and Complementary Items
Junting Wang, Chenghuan Guo, Jiao Yang +3
We study the problem of inferring substitutable and complementary items, which underpins applications such as alternative and follow-up purchase suggestions. Existing approaches ty…
LLM-RecG: A Semantic Bias-Aware Framework for Zero-Shot Sequential Recommendation
Yunzhe Li, Junting Wang, Hari Sundaram +1
Zero-shot cross-domain sequential recommendation (ZCDSR) enables predictions in unseen domains without additional training or fine-tuning, addressing the limitations of traditional…
A Pre-trained Sequential Recommendation Framework: Popularity Dynamics for Zero-shot Transfer
Junting Wang, Praneet Rathi, Hari Sundaram
Sequential recommenders are crucial to the success of online applications, \eg e-commerce, video streaming, and social media. While model architectures continue to improve, for eve…
Pre-trained Neural Recommenders: A Transferable Zero-Shot Framework for Recommendation Systems
Junting Wang, Adit Krishnan, Hari Sundaram +1
Modern neural collaborative filtering techniques are critical to the success of e-commerce, social media, and content-sharing platforms. However, despite technical advances -- for…