15 citations · 15 across the 4 of their papers we have counts for
6 papers
MIRA: Empowering One-Touch AI Services on Smartphones with MLLM-based Instruction Recommendation
Zhipeng Bian, Jieming Zhu, Xuyang Xie +3
The rapid advancement of generative AI technologies is driving the integration of diverse AI-powered services into smartphones, transforming how users interact with their devices.…
RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation
Sashuai Zhou, Weinan Gan, Qijiong Liu +7
Recent advances in LLM-based recommendation have shown promise, yet their cross-domain generalization is hindered by a fundamental mismatch between language-centric pretraining and…
Open-set Cross Modal Generalization via Multimodal Unified Representation
Hai Huang, Yan Xia, Shulei Wang +6
This paper extends Cross Modal Generalization (CMG) to open-set environments by proposing the more challenging Open-set Cross Modal Generalization (OSCMG) task. This task evaluates…
Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations
Hai Huang, Yan Xia, Sashuai Zhou +3
Domain Generalization (DG) aims to enhance model robustness in unseen or distributionally shifted target domains through training exclusively on source domains. Although existing D…
Continual Cross-Modal Generalization
Yan Xia, Hai Huang, Minghui Fang +1
Cross-modal generalization aims to learn a shared discrete representation space from multimodal pairs, enabling knowledge transfer across unannotated modalities. However, achieving…
EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration
Minjie Hong, Yan Xia, Zehan Wang +8
Large language models (LLMs) are increasingly leveraged as foundational backbones in the development of advanced recommender systems, offering enhanced capabilities through their e…