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20202024
most citedAdapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

18 citations · 21 across the 9 of their papers we have counts for

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Showing cs.IRShow all

7 papers · 1 filter

cs.IR2024

Why Not Together? A Multiple-Round Recommender System for Queries and Items

Jiarui Jin, Xianyu Chen, Weinan Zhang +2

A fundamental technique of recommender systems involves modeling user preferences, where queries and items are widely used as symbolic representations of user interests. Queries de…

cs.IR20233 cited

Lending Interaction Wings to Recommender Systems with Conversational Agents

Jiarui Jin, Xianyu Chen, Fanghua Ye +5

Recommender systems trained on offline historical user behaviors are embracing conversational techniques to online query user preference. Unlike prior conversational recommendation…

cs.IR2023

Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank

Jiarui Jin, Xianyu Chen, Weinan Zhang +5

Learning-to-rank is a core technique in the top-N recommendation task, where an ideal ranker would be a mapping from an item set to an arrangement (a.k.a. permutation). Most existi…

cs.IR2023

Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation

Xianyu Chen, Jian Shen, Wei Xia +9

With the development of the online education system, personalized education recommendation has played an essential role. In this paper, we focus on developing path recommendation s…

cs.IR2022

Who to Watch Next: Two-side Interactive Networks for Live Broadcast Recommendation

Jiarui Jin, Xianyu Chen, Yuanbo Chen +5

With the prevalence of live broadcast business nowadays, a new type of recommendation service, called live broadcast recommendation, is widely used in many mobile e-commerce Apps.…

cs.IR2022

Learn over Past, Evolve for Future: Search-based Time-aware Recommendation with Sequential Behavior Data

Jiarui Jin, Xianyu Chen, Weinan Zhang +3

The personalized recommendation is an essential part of modern e-commerce, where user's demands are not only conditioned by their profile but also by their recent browsing behavior…