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Evaluation & Benchmarksaka OpenJevaka authored144

SemIf

SemIf is an open-source decision-scoring project (formerly OpenJev) that evaluates runtime-defined yes/no, choice, and rubric questions by reading option logits from open models instead of generating JSON text.

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The project ships reproducible benchmarks including authored144.jsonl (144 labeled decision rows) and a larger frozen evaluation matrix, and documents direct-readout speed advantages over compact JSON generation on shared Qwen3.5-4B weights. LangChain hosts a gateway model semif-qwen3.5-4b aligned with the System One API; it is independent of TypeSafe AI's commercial Jev service.

Related terms

AI BenchmarkJevRHAE (Relative Human Action Efficiency)Ground TruthMRCRMassive Text Embedding Benchmark