AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora
Summary: AgenticScholar integrates structure-aware scholarly representations, LLM-driven hybrid query planning, and composable execution into an agentic data-management system. It converts natural-language queries into interpretable DAG pipelines for scalable retrieval, reasoning, discovery, and generation over multimodal corpora. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Hai Lan (University of Queensland)
- 2. Tingting Wang (University of Queensland)
- 3. Zhifeng Bao (University of Queensland)
- 4. Guoliang Li (Tsinghua University)
- 5. Daomin Ji (University of Queensland)
- 6. Ge Lee (University of Queensland)
- 7. Feng Luo (University of Queensland)
- 8. Zi Huang (University of Queensland)
- 9. Hailang Qiu (Wuhan University)
- 10. Gang Hua (Wuhan University)
BibTeX Citation
@inproceedings{lan_sigmod26,
title = {{AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora}},
author = {Lan, Hai and Wang, Tingting and Bao, Zhifeng and Li, Guoliang and Ji, Daomin and Lee, Ge and Luo, Feng and Huang, Zi and Qiu, Hailang and Hua, Gang},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802008},
url = {https://dl.acm.org/doi/10.1145/3802008},
year = {2026}
}
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