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TERAG: Token-Efficient Graph-Based Retrieval-Augmented Generation Permalink
Preprint, arXiv:2509.18667, 2025
A token-efficient framework for graph construction and retrieval-augmented generation.
Recommended citation: Qiao Xiao, Hong Ting Tsang, and Jiaxin Bai. 2025. TERAG: Token-Efficient Graph-Based Retrieval-Augmented Generation. arXiv:2509.18667.
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SING: Synthetic Intention Graph for Scalable Active Tool Discovery in LLM Agents Permalink
Preprint, arXiv:2606.16591, 2026
An intention-aware framework for active tool discovery in large language model agents.
Recommended citation: Qiao Xiao, Haochen Shi, Yisen Gao, Wenbin Hu, Huihao Jing, Tianshi Zheng, Baixuan Xu, Ziheng Zhang, Weiqi Wang, Haoran Li, Jiaxin Bai, and Yangqiu Song. 2026. SING: Synthetic Intention Graph for Scalable Active Tool Discovery in LLM Agents. arXiv:2606.16591.
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AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction Permalink
Published in ACL 2026, 2026
Optimizing knowledge graph construction for downstream retrieval-augmented question answering with reinforcement learning.
Recommended citation: Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, Qiao Xiao, Tianshi Zheng, Baixuan Xu, Shujie Liu, and Yangqiu Song. 2026. AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction. Proceedings of ACL 2026, 23351–23374.
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