5 citations · 11 across the 15 of their papers we have counts for
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cs.IR2024
QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou
Xinchen Luo, Jiangxia Cao, Tianyu Sun +17
In recent years, with the significant evolution of multi-modal large models, many recommender researchers realized the potential of multi-modal information for user interest modeli…
cs.AI2024
ELASTIC: Efficient Linear Attention for Sequential Interest Compression
Jiaxin Deng, Shiyao Wang, Song Lu +5
State-of-the-art sequential recommendation models heavily rely on transformer's attention mechanism. However, the quadratic computational and memory complexities of self attention…
cs.CL2024★ 5 cited
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model
Xinrun Du, Zhouliang Yu, Songyang Gao +11
In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs. Uniquely initiate…