5 citations · 5 across the 4 of their papers we have counts for
5 papers
Kwai Summary Attention Technical Report
Chenglong Chu, Guorui Zhou, Guowang Zhang +35
Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic understanding/reasoning, code agen…
ReST: A Plug-and-Play Spatially-Constrained Representation Enhancement Framework for Local-Life Recommendation
Hao Jiang, Long Zhang, Guoquan Wang +6
Local-life recommendation have witnessed rapid growth, providing users with convenient access to daily essentials. However, this domain faces two key challenges: (1) spatial constr…
Short Video Segment-level User Dynamic Interests Modeling in Personalized Recommendation
Zhiyu He, Zhixin Ling, Jiayu Li +5
The rapid growth of short videos has necessitated effective recommender systems to match users with content tailored to their evolving preferences. Current video recommendation mod…
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…
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…