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johnhughes3/LegalForecastBench

Benchmark that tests whether models can forecast federal motion-to-dismiss rulings from the judge's written record, scored with claim-defendant micro-Brier metrics and clustered intervals. Ships a Jev integration under integrations/jev alongside the frontier-model workflows.

johnhughes3/LegalForecastBench on GitHub

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5
Forks
1
Language
Python
License
Apache-2.0
Last push
24 Sep 2026

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How it uses Jev

    record.pop("long_context_surcharge", None)
else:
    direct_typesafe = provider == "typesafe"
    record = {
        "provider": provider,
        "model_id": "jev-1.13.0" if direct_typesafe else "typesafe-ai/jev",
        "display_name": (
            "Jev ("
            + ("Grok 4.6" if summary_model == "grok" else "Luna")
            + (
                " shorter summaries; one shot)"
                if short_summaries
                else " summaries; one shot)"
            )
            if path

View in legalforecast/cli_commands/jev.py

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