2 citations · 2 across the 7 of their papers we have counts for
7 papers · 1 filter
Agentic Transaction: Towards ACID-Compliant Agent Systems
Zhaoyan Sun, Xiaoxiao Wang, Guoliang Li
Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasoning, tool use, code generation,…
AgenticDataBench: A Comprehensive Benchmark for Data Agents
Zhaoyan Sun, Shan Zhong, Daizhou Wen +10
Data science aims to derive actionable insights from heterogeneous raw data, unlocking the value of the massive amounts of data generated in modern society. Automating this process…
PrepBench: How Far Are We from Natural-Language-Driven Data Preparation?
Jingzhe Xu, Rui Wang, Jiannan Wang +1
Data preparation is a central and time-consuming stage in data analysis workflows. Traditionally, commercial tools have relied on graphical user interfaces (GUIs) to simplify data…
AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora
Hai Lan, Tingting Wang, Zhifeng Bao +7
Managing the rapidly growing scholarly corpus poses significant challenges in representation, reasoning, and efficient analysis. An ideal system should unify structured knowledge m…
Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities
Jean-Daniel Fekete, Yifan Hu, Dominik Moritz +8
The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era…
AgenticData: An Agentic Data Analytics System for Heterogeneous Data
Ji Sun, Guoliang Li, Peiyao Zhou +3
Existing unstructured data analytics systems rely on experts to write code and manage complex analysis workflows, making them both expensive and time-consuming. To address these ch…
Data Agent: A Holistic Architecture for Orchestrating Data+AI Ecosystems
Zhaoyan Sun, Jiayi Wang, Xinyang Zhao +2
Traditional Data+AI systems utilize data-driven techniques to optimize performance, but they rely heavily on human experts to orchestrate system pipelines, enabling them to adapt t…