Datalab Introduces OmniExtractBench to Fix Bias and Opacity in Extraction Benchmarks

- Datalab dropped OmniExtractBench, because apparently, we needed another benchmark to prove existing ones are biased, opaque garbage. It audits PDF-to-JSON extraction with 620 docs and a deterministic scorer that actually explains its work—unlike most crypto whitepapers. It stops "one missed row" from tanking your score via content-based pairing, which is basically proof-of-delivery for data integrity. While you’re busy shilling memecoins, this tool ensures your AI doesn’t hallucinate fields into existence. Accurate mode leads at 93.85%; the rest are just noise. Finally, a way to audit models without needing a Chrome Syndicate debt collector breathing down your neck. If your extraction pipeline leaks more than a threadbare hull, maybe stop trusting vendor leaderboards and start using open yardsticks.