A Judge-Aware Gated Multi-Task Learning architecture with outcome taxonomy supervision achieves SOTA accuracy on 13,937 UK Employment Tribunal decisions using an order of magnitude fewer parameters than generative SFT baselines on a 26B model.
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Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning
A Judge-Aware Gated Multi-Task Learning architecture with outcome taxonomy supervision achieves SOTA accuracy on 13,937 UK Employment Tribunal decisions using an order of magnitude fewer parameters than generative SFT baselines on a 26B model.