New Benchmark Evaluates LLM Agents on Financial Spreadsheet Tasks
Researchers have introduced WorkstreamBench, a benchmark designed to evaluate LLM agents on end-to-end spreadsheet tasks in finance. The benchmark addresses a gap in existing evaluations, which focus on question-answering or single-formula edits, by assessing agents' ability to construct complete spreadsheets from high-level instructions. WorkstreamBench targets economically critical workflows such as financial modeling, forecasting, and scenario analysis. The evaluation criteria include high-level qualities like readability and ease of modification, reflecting real-world review processes. The work is described in arXiv paper 2605.22664.
Key facts
- WorkstreamBench evaluates LLM agents on end-to-end spreadsheet tasks.
- The benchmark focuses on financial workflows like modeling and scenario analysis.
- Existing benchmarks only cover question-answering or single-formula edits.
- The evaluation criteria include readability and ease of modification.
- The research is presented in arXiv paper 2605.22664.
- LLM agents are expected to produce complete artifacts from user instructions.
- Frontier AI labs have developed agents that can construct entire spreadsheets.
- Finance is a key domain for spreadsheet-based workflows.
Entities
Institutions
- arXiv