Official repository for DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
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Updated
Apr 6, 2026 - Python
Official repository for DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
Evaluation for AI outputs against trusted educational rubrics. Measure and improve content quality with research-backed rubrics — ensuring rigor, reliability, and alignment to classroom needs.
Export grades from assignment using advanced grading methods in excel format
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R script to transform a .xlsx workbook into a PDF or HTML with rubrics and assessment-forms for academic courses. Currently in Dutch. Written for a theology program @ Protestant Theological University
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Evidence-backed quality control for LLM outputs: rubrics, claim grounding, safety gates, human review, and reports.
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📊 Generate and access a comprehensive rubric dataset with RubricHub, enhancing your evaluation processes through automated data synthesis.
Prompt and AI-output evaluation case studies for hallucination risk, localization, rubrics, and QA.
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Rubric-as-judge runner using the Anthropic Python SDK with tool-use API for schema-validated structured output. 17 mocked tests included.
K–12 LLM evaluation examples using teacher-centered ground truths, rubrics, and tone-aware response review.
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