Publications

You can also find my articles on my Google Scholar profile.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation

Published in The 23rd CCF Conference on Web Information Systems and Applications, 2026

NGM-RAG is a novel RAG framework combined with graph structure, which improves the retrieval and generation effects in multi-hop reasoning and complex question-answering tasks by integrating multiple matching methods.

RISE: A Retrieval-Augmented Generation Enhanced Immersive System for Education

Published in Companion Proceedings of the ACM Web Conference, 2026

We have developed an immersive education system based on RAG, MCP, and virtual digital humans.

Recommended citation: Chen, G., Tang, H., Wei, Y., Wang, Y., Zhang, H., Hou, Y., Zheng, M., & Huang, J. (2026). RISE: A Retrieval-Augmented Generation Enhanced Immersive System for Education. In Companion Proceedings of the ACM Web Conference 2026, 85–88.
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LiR^3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation

Published in The Association for the Advancement of Artificial Intelligence, 2026

We explored the reasoning strategies of reasoning models in RAG multi-hop QA tasks, finally proposed a lightweight framework that improves performance while significantly reducing reasoning overhead by integrating three modules.

Recommended citation: Chen, G., Huang, J., Xie, H., Sun, F., & Jia, T. (2026). LiR3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation. In Proceedings of the AAAI Conference on Artificial Intelligence, 40(36), 30201–30209.
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