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Crypto Accounting Bench: Evaluating Frontier and Open-Weight Models on Crypto-Asset Accounting Tasks

arXiv 2609.14811 ↗First posted 13 Sep 2026cs.AI cs.CLcited by 0

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Abstract (arXiv)

We introduce Crypto Accounting Bench (CAB), a benchmark for assessing whether frontier and open-weight language models can reconstruct the complete journal entry that an organization actually posted for a crypto-asset transaction. CAB contains 118 evaluation tasks drawn from 7 pseudonymized organizations. Each task combines transaction mechanics, asset quantities and base-currency values, wallet and legal-entity context, counterparty evidence, related transaction legs, recurrence, tax-lot evidence, and the organization's complete chart of accounts. The target is a balanced structured entry with every required account, side, amount, currency, and full-precision asset quantity. We evaluate 12 models spanning proprietary frontier systems and open-weight releases over 3 independent attempts per task, producing 4,248 trajectories. We report 3 metrics: Mean Score, Best@3, and Pass@3. Pass@3 is the fraction of tasks with at least 1 of 3 attempts that satisfies every rubric criterion and required gate. The leading model reaches 77.43% Mean Score, while the best Pass@3 is 56.78%. Deterministic diagnostics, read from each task's best of 3 attempts and macro-averaged across the 12 models, show higher base-amount agreement (97.8%) than deciding-account accuracy (56.3%). Together with the failure analysis, these results identify account selection and complete-entry composition as the main remaining challenges on CAB.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 13 Sep 2026.

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References · 3

  1. 2025GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Taskscited by 158
  2. 2025FinMaster: A Holistic Benchmark for Mastering Full-Pipeline Financial Workflows with LLMscited by 9
  3. 2026FinBalance: A Multi-Document Accounting Reconciliation Benchmarkcited by 3

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