5 papers
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…
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…
VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context Videos
Xubin Ren, Lingrui Xu, Long Xia +3
Retrieval-Augmented Generation (RAG) has demonstrated remarkable success in enhancing Large Language Models (LLMs) through external knowledge integration, yet its application has p…
RecLM: Recommendation Instruction Tuning
Yangqin Jiang, Yuhao Yang, Lianghao Xia +3
Modern recommender systems aim to deeply understand users' complex preferences through their past interactions. While deep collaborative filtering approaches using Graph Neural Net…