2 papers
cs.IR2024
A Practice-Friendly LLM-Enhanced Paradigm with Preference Parsing for Sequential Recommendation
Dugang Liu, Shenxian Xian, Xiaolin Lin +5
The training paradigm integrating large language models (LLM) is gradually reshaping sequential recommender systems (SRS) and has shown promising results. However, most existing LL…
cs.IR2023
Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset
Dugang Liu, Pengxiang Cheng, Zinan Lin +6
Debiased recommendation with a randomized dataset has shown very promising results in mitigating the system-induced biases. However, it still lacks more theoretical insights or an…