9 citations · 16 across the 7 of their papers we have counts for
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cs.IR2026
Tlow: Flow-based Item Tokenizer for Recommendation
Nian Li, Chonggang Song, Jingtao Ding +3
Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundamentally addressing the problems…
cs.IR2025★ 1 cited
Simulating Filter Bubble on Short-video Recommender System with Large Language Model Agents
Nicholas Sukiennik, Haoyu Wang, Zailin Zeng +2
An increasing reliance on recommender systems has led to concerns about the creation of filter bubbles on social media, especially on short video platforms like TikTok. However, th…
cs.IR2024★ 9 cited
Modeling User Fatigue for Sequential Recommendation
Nian Li, Xin Ban, Cheng Ling +6
Recommender systems filter out information that meets user interests. However, users may be tired of the recommendations that are too similar to the content they have been exposed…