arXiv:2602. 16720v2 Announce Type: replace-cross Abstract: Text-to-SQL systems powered by Large Language Models have excelled on academic benchmarks but struggle in complex enterprise environments.
By Bowen Cao, Weibin Liao, Yushi Sun, Dong Fang, Haitao Li, Wai Lam
arXiv:2606. 18108v1 Announce Type: cross Abstract: We develop a text-to-SQL (structured query language) system based on large language models (LLMs) using in-context learning and apply it to the Automatic Learning for the Rapid Classification of Events (ALeRCE) astronomical database.
By P. A. Estevez, J. Espejo-Moreira, S. Sanfeliu-Alvarez, F. Forster, A. M. Munoz Arancibia, G. Cabrera-Vives, F. E. Bauer, A. Bayo, M. Catelan, R. Dastidar, L. Hernandez-Garcia, J. A. Intriago, G. Pignata
arXiv:2609.21133v1 Announce Type: cross
Abstract: SQL has been augmented with AI operators, enabling modern data analytics platforms to derive insights from both structured and unstructured data. We...
By Tarfah Alrashed, Fatma Ozcan, Per Jacobsson, Tal Neiman, Xianshun Chen
The paper introduces EXYGEN, a framework that enables conversational access to large knowledge graphs by combining VoID descriptions, ShEx schemas, retrieved triples, and example question‑query pairs in a retrieval‑augmented generation pipeline. On the SciQA benchmark, this approach achieves an exact‑match score of 0.419 without fine‑tuning any large language model, and shows that larger general‑purpose LLMs can outperform smaller code‑specialized ones when provided sufficient context. To scale metadata generation for very large KGs, the authors propose a predicate‑coverage‑aware parallel graph sampling strategy that preserves structural diversity, reduces runtime by over 80× on OpenCitations Meta and GESIS, and is the only tractable method for obtaining complete metadata on ORKG.
By Harshdeep Singh, Yurui Zhu, Giovanni Colavizza, Matteo Romanello
arXiv:2608.29345v1 Announce Type: new
Abstract: While recent Large Language Model (LLM)-based text-to-SQL systems achieve impressive performance on standard benchmarks, they struggle when user querie...
By Yunfan Zhou, Qiming Shi, Yizhou Yang, Di Weng, Yingcai Wu
arXiv:2602.05385v2 Announce Type: replace
Abstract: Text-to-SQL is a key natural language processing task that maps natural language questions to SQL queries, enabling intuitive interaction with web-...
By Tao Liu, Jiafan Lu, Bohan Yu, Pengcheng Wu, Liu Haixin, Guoyu Xu, Li Xiangheng, Lixiao Li, Jiaming Hou, Zhao Shijun, Xinglin Lyu, Kunli Zhang, Yuxiang Jia, Hongyin Zan