Towards Verifiable Agentic Data Science: Solving Irregular TSQA Via Tool-Grounded Reasoning

Computer Science > Artificial Intelligence [Submitted on 13 Jun 2026] Towards Verifiable Agentic Data Science: Solving Irregular TSQA Via Tool-Grounded Reasoning Sanhorn Chen, Xiaoyang Chen, Boyu Liu, Roy Zhao Time series data in real-world deployments is overwhelmingly irregular. Observations are asynchronous, missing values are informative rather than random, and sampling frequencies vary across sensors and operational windows. However, existing Time Series Question Answering (TSQA) benchmarks mostly assume regularly sampled inputs, leaving a fundamental gap in understanding how large language models (LLMs) and AI agents perform under irregular conditions. To bridge this gap, we introduce IRTS-ToolBench, a benchmark of 1,700 questions spanning 10 task types across 13 domains. IRTS-ToolBench is designed to be used independently by any researcher working on LLM-based irregular time series analysis, providing standardized inputs and a reproducible evaluation protocol. Code can be found in this https URL. Comments: 15 pages Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2606.15107 [cs.AI]   (or arXiv:2606.15107v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.15107 Focus to learn more Submission history From: Sanhorn Chen [view email] [v1] Sat, 13 Jun 2026 04:41:04 UTC (9,686 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)