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This preprint presents a benchmark that assesses mathematical reasoning in chat-based LLMs, suggesting improvements for accuracy and reliability.
This preprint presents a UI-native benchmark for evaluating mathematical reasoning in chat-based large language model (LLM) systems. The benchmark is derived from the published puzzle codex Vault of Echoes: Volume I and evaluates single-shot (pass@1) performance under strict output directives across contemporary chat products. We report accuracy, uncertainty estimates, and UI-layer failure modes, and release a machine-readable evaluation ledger to support reproducibility.
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Paudel et al. (2026) studied this question.
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