235 citations
- Zhejiang UniversityCN19 papers
- University of MichiganUS6 papers
- Tianjin UniversityCN5 papers
- Tsinghua UniversityCN5 papers
- Zhejiang University of TechnologyCN5 papers
- Nanjing UniversityCN4 papers
- Beihang UniversityCN3 papers
- Beijing Institute of TechnologyCN2 papers
- Center for Information TechnologyUS2 papers
- City University of Hong KongHK2 papers
- Fudan UniversityCN2 papers
- Hangzhou Dianzi UniversityCN2 papers
65 papers
Melo: A Production LLM-Powered Music Recommendation Agent
Shijia Wang, Da Guo, Qiang Xiao +4
We describe Melo, an LLM-powered music recommendation agent deployed on NetEase Cloud Music. Melo is structured as a deterministic five-node state graph over heterogeneous tools, w…
L2Rec: Towards Dual-View Understanding of LLMs for Personalized Recommendation
Pingjun Pan, Tingting Zhou, Peiyao Lu +3
Adapting large language models (LLMs) for personalized recommendation requires aligning their general-purpose capabilities with user-specific preferences while effectively leveragi…
A Decomposed Retrieval-Edit-Rerank Framework for Chord Generation
Qiqi He, Dichucheng Li, Xiaoheng Sun +1
Chord generation is an inherently constrained creative task that requires balancing stylistic diversity with music-theoretic feasibility. Existing approaches typically entangle can…
SELECT: Detecting Label Errors in Real-world Scene Text Data
Wenjun Liu, Qian Wu, Yifeng Hu +1
We introduce SELECT (Scene tExt Label Errors deteCTion), a novel approach that leverages multi-modal training to detect label errors in real-world scene text datasets. Utilizing an…
High-Precision and High-Efficiency Trajectory Tracking for Excavators Based on Closed-Loop Dynamics
Ziqing Zou, Cong Wang, Yue Hu +6
The complex nonlinear dynamics of hydraulic excavators, such as time delays and control coupling, pose significant challenges to achieving high-precision trajectory tracking. Tradi…
Progressive Semantic Residual Quantization for Multimodal-Joint Interest Modeling in Music Recommendation
Shijia Wang, Tianpei Ouyang, Qiang Xiao +5
In music recommendation systems, multimodal interest learning is pivotal, which allows the model to capture nuanced preferences, including textual elements such as lyrics and vario…