Benchmark: Deterministic Financial Engine Hits 100%, LLM Pipeline Fails 71%
MuhammadMujtaba21 · reddit · 2026-08-21
The author benchmarked a deterministic verification engine for AI-generated financial claims using 66 test cases. The engine passed 100% (66/66) of cases with pre-defined structured inputs, but the pass rate dropped to 29% (19/66) when using Azure OpenAI GPT-5.1 to generate live claims. Failures were concentrated in claim binding and pipeline execution rather than deterministic calculations or rule application. This suggests the verification architecture works, but the translation layer converting LLM outputs to structured claims needs improvement. The author plans to add granular diagnostics comparing expected claims, raw outputs, and normalized claims.
More from Research
- Resource: One of the most rigorous math explanations of Transformers — stanfordnlp · 2026-08-21
- CfP: Learning and Reasoning with Graphs Workshop at BNAIC '26 — pbloemesquire · 2026-08-21
- SenseTime releases open-source SenseNova U1.5 with MoT architecture — multimodalart · 2026-08-21
- DeepMind partners with game studio to explore long-term memory and multi-agent economies — GoogleDeepMind · 2026-08-21
- GigaBrain-0.7 Launch: 'System-3' Architecture Tops Robot Leaderboards — 机器之心 · 2026-08-21
- Linear Algebra Textbook 2nd Edition Adds Backpropagation & Attention — prof_g · 2026-08-21