10 papers
DeepTutor: Towards Agentic Personalized Tutoring
Bingxi Zhao, Jiahao Zhang, Xubin Ren +4
Education is one of the most promising real-world applications for Large Language Models (LLMs). However, current LLMs rely on static pre-training knowledge and lack adaptation to…
A Comprehensive Survey on Self-Supervised Learning for Recommendation
Xubin Ren, Wei Wei, Lianghao Xia +1
Recommender systems play a crucial role in tackling the challenge of information overload by delivering personalized recommendations based on individual user preferences. Deep lear…
DeepCode: Open Agentic Coding
Zongwei Li, Zhonghang Li, Zirui Guo +2
Recent advances in large language models (LLMs) have given rise to powerful coding agents, making it possible for code assistants to evolve into code engineers. However, existing m…
EasyRec: Simple yet Effective Language Models for Recommendation
Xubin Ren, Chao Huang
Deep neural networks have emerged as a powerful technique for learning representations from user-item interaction data in collaborative filtering (CF) for recommender systems. Howe…
RAG-Anything: All-in-One RAG Framework
Zirui Guo, Xubin Ren, Lingrui Xu +2
Retrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for expanding Large Language Models beyond their static training limitations. However, a critical misalig…
RecGPT: A Foundation Model for Sequential Recommendation
Yangqin Jiang, Xubin Ren, Lianghao Xia +3
This work addresses a fundamental barrier in recommender systems: the inability to generalize across domains without extensive retraining. Traditional ID-based approaches fail enti…