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20222026
most citedNExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search

3 citations · 6 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.IR2026

Learning to Retrieve from Agent Trajectories

Yuqi Zhou, Sunhao Dai, Changle Qu +3

Information retrieval (IR) systems have traditionally been designed and trained for human users, with learning-to-rank methods relying heavily on large-scale human interaction logs…

cs.IR2025

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

Changle Qu, Sunhao Dai, Ke Guo +7

Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interactions, and highly engaging user experien…

cs.IR20253 cited

NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search

Sunhao Dai, Wenjie Wang, Liang Pang +4

Generative AI search is reshaping information retrieval by offering end-to-end answers to complex queries, reducing users' reliance on manually browsing and summarizing multiple we…

cs.IR2025

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation

Jiakai Tang, Sunhao Dai, Teng Shi +5

Sequential Recommendation (SeqRec) aims to predict the next item by capturing sequential patterns from users' historical interactions, playing a crucial role in many real-world rec…

cs.IR20242 cited

Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method

Chen Yang, Sunhao Dai, Yupeng Hou +4

Reciprocal recommender systems~(RRS), conducting bilateral recommendations between two involved parties, have gained increasing attention for enhancing matching efficiency. However…

cs.IR20221 cited

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems

Yan Lyu, Sunhao Dai, Peng Wu +7

Accurate recommendation and reliable explanation are two key issues for modern recommender systems. However, most recommendation benchmarks only concern the prediction of user-item…