SIGNAL
Tracking the global AI frontier — labs · research · agents · policy
Frontier Signal
Research

SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflows

Spreadsheets are widely used for business analysis, financial modeling, reporting, and decision-making. However, most existing spreadsheet benchmarks evaluate isolated operations such as single-formula generation or local cell edits, and therefore fail to capture end-to-end workflows in realistic business settings. We introduce \textsc{SpreadsheetBench 2}, a workflow-level benchmark for spreadsheet agents that covers three task categories: generation, debugging, and visualization. The benchmark

SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflows
Primary source tldr.takara.ai ↗

Published June 29, 2026 · Category: AI Research

Overview

Spreadsheets are widely used for business analysis, financial modeling, reporting, and decision-making. However, most existing spreadsheet benchmarks evaluate isolated operations such as single-formula generation or local cell edits, and therefore fail to capture end-to-end workflows in realistic business settings. We introduce \textsc{SpreadsheetBench 2}, a workflow-level benchmark for spreadsheet agents that covers three task categories: generation, debugging, and visualization. The benchmark is constructed from authentic business data, including financial reports and corporate filings, and is annotated and validated by domain experts. The benchmark contains 321 tasks; each instance averages 11.8 worksheets and requires 593.5 cell modifications, reflecting large multi-sheet workbooks with cross-sheet dependencies. We evaluate eight frontier large language models under a unified multi-turn agent scaffold, and additionally include several LLM-based spreadsheet products as complementary baselines. Results show that current systems remain far from reliable on real-world workflows: the best model achieves 34.89\% overall task accuracy, and debugging accuracy is as low as 12.00\%. Trajectory analysis and a failure taxonomy further indicate that insufficient spreadsheet inspection and incorrect target-cell selection are the dominant bottlenecks. Together, these findings position \textsc{SpreadsheetBench 2} as a challenging testbed for advancing reliable spreadsheet automation. Project page: https://spreadsheetbench.github.io/

Source

Originally published at tldr.takara.ai.

Related Articles

F
Frontier Signal Desk

Frontier Signal tracks the global AI frontier — labs, research, agents, creation tools and real-world practice — straight from primary sources. Tip the desk: editorial@news.tunx.ai

Email the desk →
From our network: explore the AI assistant platform behind this site. Visit tunx.ai →
Note: This story is aggregated and summarized from the primary source linked above; the original publisher retains all rights. Details may evolve after publication — always confirm against the source. Nothing here is professional, legal or investment advice.

Related Stories

More from Research →