7 papers · 1 filter
CodeHID: Learning an Addressable Hierarchical Code Index for Generative Code Retrieval
Zhen Li, Yuhong Chen, Wenhao Xu +2
Code retrieval models have predominantly relied on a flat matching paradigm that treats code snippets as independent candidates, making them less capable of distinguishing similar…
Knowledge-Geometry Decoupling: Refreshable Pretrained Transfer for Streaming Recommendation
Zixuan Wang, Yuhong Chen, Yuxuan Zhu +10
Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and h…
RAIE: Region-Aware Incremental Preference Editing with LoRA for LLM-based Recommendation
Jin Zeng, Yupeng Qi, Hui Li +4
Large language models (LLMs) are increasingly adopted as the backbone of recommender systems. However, user-item interactions in real-world scenarios are non-stationary, making pre…
AgenticRec: A Recommendation-Oriented Agentic Framework with Progressive Tool-Integrated Reasoning Optimization
Tianyi Li, Zixuan Wang, Guidong Lei +2
Recommender agents built on Large Language Models offer a promising paradigm for personalized recommendation. However, existing agents typically suffer from a misalignment between…
ManCAR: Manifold-Constrained Latent Reasoning with Adaptive Test-Time Computation for Sequential Recommendation
Kun Yang, Yuxuan Zhu, Yazhe Chen +7
Sequential recommendation increasingly employs latent multi-step reasoning to enhance test-time computation. Despite empirical gains, existing approaches largely drive intermediate…
Retrieval-Augmented Recommendation Explanation Generation with Hierarchical Aggregation
Bangcheng Sun, Yazhe Chen, Jilin Yang +2
Explainable Recommender System (ExRec) provides transparency to the recommendation process, increasing users' trust and boosting the operation of online services. With the rise of…