46 citations · 47 across the 4 of their papers we have counts for
4 papers
Towards An Efficient LLM Training Paradigm for CTR Prediction
Allen Lin, Renqin Cai, Yun He +5
Large Language Models (LLMs) have demonstrated tremendous potential as the next-generation ranking-based recommendation system. Many recent works have shown that LLMs can significa…
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts
Xiangjue Dong, Yun He, Ziwei Zhu +1
A key component of modern conversational systems is the Dialogue State Tracker (or DST), which models a user's goals and needs. Toward building more robust and reliable DSTs, we in…
Evolution of Popularity Bias: Empirical Study and Debiasing
Ziwei Zhu, Yun He, Xing Zhao +1
Popularity bias is a long-standing challenge in recommender systems. Such a bias exerts detrimental impact on both users and item providers, and many efforts have been dedicated to…
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks
Yun He, Xue Feng, Cheng Cheng +3
In many personalized recommendation scenarios, the generalization ability of a target task can be improved via learning with additional auxiliary tasks alongside this target task o…