FairEval: Human-Aligned Evaluation for Generative Models

• LLM-as-Judge alignment scoring
• Toxicity / safety analysis
• Human agreement metrics (κ, ρ)
• Group-wise fairness dashboards

What this repo contains

• The FairEval evaluation pipeline (code on GitHub)
• A planned Hugging Face Space demo (UI built in Streamlit)
• Links to my preprint and Medium explainer.

Code: https://github.com/kritibehl/FairEval
Medium: https://medium.com/@kriti0608/faireval-a-human-aligned-evaluation-framework-for-generative-models-d822bfd5c99d

Capabilities

1. Rubric-based LLM-as-Judge scoring
   • Uses a structured rubric (config/prompts/judge_rubric.md) to score:
     • coherence
     • helpfulness
     • factuality
   • Returns scalar scores that correlate with human preference.
2. Toxicity and safety metrics
   • Wraps a toxicity model (e.g., Detoxify) to compute:
     • composite toxicity
     • per-category scores (insult, threat, identity attack, etc.)
   • Provides Altair charts for:
     • toxicity breakdown by category
     • toxicity distribution by demographic group
3. Human evaluation agreement
   • Ingests a human_eval.csv file with human ratings.
   • Computes:
     • Fleiss’ κ (inter-rater reliability)
     • Spearman ρ between judge and human scores.

Example Usage