2 citations · 3 across the 9 of their papers we have counts for
9 papers
Are Recommenders Self-Aware? Label-Free Recommendation Performance Estimation via Model Uncertainty
Jiayu Li, Ziyi Ye, Guohao Jian +4
Can a recommendation model be self-aware? This paper investigates the recommender's self-awareness by quantifying its uncertainty, which provides a label-free estimation of its per…
Short Video Segment-level User Dynamic Interests Modeling in Personalized Recommendation
Zhiyu He, Zhixin Ling, Jiayu Li +5
The rapid growth of short videos has necessitated effective recommender systems to match users with content tailored to their evolving preferences. Current video recommendation mod…
Evaluating Intelligence via Trial and Error
Jingtao Zhan, Jiahao Zhao, Jiayu Li +7
Intelligence is a crucial trait for species to find solutions within a limited number of trial-and-error attempts. Building on this idea, we introduce Survival Game as a framework…
ReChorus2.0: A Modular and Task-Flexible Recommendation Library
Jiayu Li, Hanyu Li, Zhiyu He +4
With the applications of recommendation systems rapidly expanding, an increasing number of studies have focused on every aspect of recommender systems with different data inputs, m…
Introducing EEG Analyses to Help Personal Music Preference Prediction
Zhiyu He, Jiayu Li, Weizhi Ma +3
Nowadays, personalized recommender systems play an increasingly important role in music scenarios in our daily life with the preference prediction ability. However, existing method…
Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation
Hanyu Li, Weizhi Ma, Peijie Sun +6
Cross-domain recommender (CDR) systems aim to enhance the performance of the target domain by utilizing data from other related domains. However, irrelevant information from the so…
A Situation-aware Enhancer for Personalized Recommendation
Jiayu Li, Peijie Sun, Chumeng Jiang +3
When users interact with Recommender Systems (RecSys), current situations, such as time, location, and environment, significantly influence their preferences. Situations serve as t…
Recommender for Its Purpose: Repeat and Exploration in Food Delivery Recommendations
Jiayu Li, Aixin Sun, Weizhi Ma +2
Recommender systems have been widely used for various scenarios, such as e-commerce, news, and music, providing online contents to help and enrich users' daily life. Different scen…
Intent-aware Ranking Ensemble for Personalized Recommendation
Jiayu Li, Peijie Sun, Zhefan Wang +5
Ranking ensemble is a critical component in real recommender systems. When a user visits a platform, the system will prepare several item lists, each of which is generally from a s…