Oct 20, 2023 · We propose a novel Unified pre-trained language model enhanced sequential recommendation (UPSR), aiming to build a unified pre-trained recommendation model for ...
Nov 27, 2023 · To bridge the gap, we propose a novel unified pre-trained language model enhanced sequential recommendation (UPSR) that thoroughly transfers the ...
Ideally, the textual representation should be like natural language. (to better extract knowledge from PLM), domain-consistent (to be smoothly adapted to other ...
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The Elephant in the Room: Rethinking the Usage of Pre-trained Language Model in Sequential Recommendation · Thoroughly Modeling Multi-domain Pre-trained ...
Foundation models for Recommender System Paper List - GitHub
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Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language, arxiv 2023/10, [paper]; MISSRec: Pre-training and Transferring Multi-modal Interest ...
Oct 27, 2023 · [1] Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language. This paper from Tencent introduces UPSR, a Unified pre-trained ...
Oct 21, 2024 · Learning high-quality item embeddings is crucial for recommendation tasks such as matching and ranking. However, existing methods often rely ...
Jul 28, 2024 · This article delves deep into the intricate processes of pre-training and fine-tuning LLMs for recommender systems, offering a thorough exploration of cutting- ...
This work proposes the development of a multimodal foundation model (MFM) considering visual, textual, and personalization modalities under the P5 ...
Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language · pdf icon · hmtl icon · Zekai Qu, Ruobing Xie, Chaojun Xiao, Yuan Yao, Zhiyuan Liu ...