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Large Language Models (LLMs) have recently emerged as promising tools for recommendation thanks to their advanced textual understanding ability and context-awareness.
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Task Relation-aware Continual User Representation Learning. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1107–1119
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Collaborative Alignment for Recommendation. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (Boise, ID, USA) (CIKM ’24) . Association for Computing Machinery, New York, NY, USA, 2315–2325
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Dynamic Time-aware Continual User Representation Learning
Seungyoon Choi, Sein Kim, Hongseok Kang, Wonjoong Kim, and Chanyoung Park. 2025 · 2025
Closest in time.
Disentangling and Generating Modalities for Recommendation in Missing Modality Scenarios
Jiwan Kim, Hongseok Kang, Sein Kim, Kibum Kim, and Chanyoung Park. 2025 · 2025
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