arXiv:2606. 05679v1 Announce Type: cross Abstract: Agents increasingly generate SQL, orchestrate pipelines, and automate data analysis on behalf of users.
By Charlie Summers, Eugene Wu
arXiv:2606. 08661v1 Announce Type: cross Abstract: Data agents integrate LLM-driven reasoning with relational data access, executable analytical tools, and multi-step workflow orchestration, making them increasingly central to enterprise analytics.
By Kuncan Wang, Ziting Wang, Peizhuo Lv, Haoyang Li, Guoliang Li, Gao Cong, Wei Dong
arXiv:2605. 21027v2 Announce Type: replace-cross Abstract: Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional business intelligence tools or Text-to-SQL systems.
By Gundeep Singh, Parsa Kavehzadeh, Jing Xia, Xue-Yong Fu, Julien Bouvier Tremblay, Md Tahmid Rahman Laskar, Vincent Lum, Shashi Bhushan TN
arXiv:2606. 26627v1 Announce Type: cross Abstract: Large language model agents increasingly query databases, search document collections, call external APIs, remember past interactions, and act on a user's behalf.
By Nada Lahjouji, Ashwin Gerard Colaco
arXiv:2604. 14401v2 Announce Type: replace Abstract: Agentic AI systems are becoming commonplace in domains that require long-lived, stateful decision-making in continuously evolving conditions.
By Duo Lu, Andrew Crotty, U\u{g}ur \c{C}etintemel
arXiv:2608. 13900v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasoning, tool use, code generation, and workspace manipulation.
By Zhaoyan Sun, Xiaoxiao Wang, Guoliang Li