RISE: A Retrieval-Augmented Generation Enhanced Immersive System for Education
Published in The Web Conference Demo, 2026
We have developed an immersive education system based on RAG, MCP, and virtual digital humans.
Published in The Web Conference Demo, 2026
We have developed an immersive education system based on RAG, MCP, and virtual digital humans.
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., and Jia, T. (2025). LIR3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation. arXiv preprint arXiv:2512.18329.
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