V-FiLLM: Verified Financial LLM Reasoning Benchmark
While existing benchmarks have made substantial progress in evaluating LLMs across STEM domains, financial reasoning over structured data remains comparatively less explored. We introduce V-FiLLM, a framework that generates financial reasoning benchmarks from executable computation trees grounded in real tables, yielding items whose answers are correct by construction. Trees are evaluated symbolically to obtain ground truth and rendered into natural-language questions, removing any model from the labeling loop, so items can be generated at arbitrary scale without annotation cost and without inheriting a generator's error rate. V-FiLLM exposes four independently controllable axes of diffic...
| Authors | Alicia Larsen, Victoire Laurent, Aulia Kharis Rakhmasari et al. |
|---|---|
| Primary category | cs.AI |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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