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TaxCalcBench: Evaluating Frontier Models on the Tax Calculation Task

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arxiv 2507.16126 v1 pith:ZSVSSOCY submitted 2025-07-22 cs.AI

TaxCalcBench: Evaluating Frontier Models on the Tax Calculation Task

classification cs.AI
keywords incomemodelscalculationpersonaltaskcalculatingreturnstaxcalcbench
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Can AI file your taxes? Not yet. Calculating US personal income taxes is a task that requires building an understanding of vast amounts of English text and using that knowledge to carefully compute results. We propose TaxCalcBench, a benchmark for determining models' abilities to calculate personal income tax returns given all of the necessary information. Our experiment shows that state-of-the-art models succeed in calculating less than a third of federal income tax returns even on this simplified sample set. Our analysis concludes that models consistently misuse tax tables, make errors in tax calculation, and incorrectly determine eligibility. Our findings point to the need for additional infrastructure to apply LLMs to the personal income tax calculation task.

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  1. Interactive Critique-Revision Training for Reliable Structured LLM Generation

    cs.LG 2026-05 unverdicted novelty 5.0

    DPA-GRPO trains a generator-verifier pair via group-relative policy optimization on paired counterfactual actions, improving structured output accuracy on TaxCalcBench over zero-shot and generator-only baselines.