Topic
LLM-as-a-Judge Techniques
13 posts on llm-as-a-judge techniques — part of developer tools on the n4n AI blog.
When to use LLM-as-a-judge instead of exact-match scoring
A practical guide to deciding between LLM-as-a-judge vs exact-match scoring for evaluation pipelines, with code, tradeoffs, and pitfalls.
What is LLM-as-a-judge, and when should you trust it
What is LLM-as-a-judge? This explainer defines using language models to score or judge AI outputs, covers how it works, when to trust it, and pitfalls.
Using GPT-4o as a judge for summarization quality
Step-by-step tutorial: implement GPT-4o as a judge for summarization quality with Python, scoring rubrics, and fallback for rate limits via API.
Single-answer grading vs pairwise comparison for LLM judges
A head-to-head comparison of single-answer vs pairwise LLM judge methods across cost, latency, ergonomics, and limits for eval pipelines.
Self-preference bias in LLM-as-a-judge scoring
Self-preference bias in LLM-as-a-judge scoring distorts eval metrics. Learn how to detect it and architect unbiased judge pools with concrete code.
Reducing position bias in LLM-as-a-judge comparisons
Step-by-step methodology for reducing position bias LLM judge comparisons including prompt swapping, multi-judge ensembles, and Python code.
Multi-judge ensembles for more reliable LLM evaluation
Step-by-step guide to multi-judge ensembles LLM evaluation: assemble diverse judges, aggregate scores, measure agreement, and avoid deployment pitfalls.
LLM-as-a-judge vs human evaluation: cost vs accuracy
A practical head-to-head of LLM-as-a-judge vs human evaluation across cost, latency, and accuracy, with a clear verdict for engineering teams shipping LLM features.
Fine-tuning a smaller model to act as an LLM judge
Step-by-step tutorial on fine-tuning a smaller model as LLM judge: generate preference data, train a LoRA adapter on Mistral-7B, and validate accuracy.
Common failure modes of LLM-as-a-judge pipelines
An analysis of the failure modes LLM-as-a-judge pipelines encounter in production, with concrete examples and tradeoffs for engineers building eval systems.
Chain-of-thought prompting for more consistent LLM judges
Learn how to build a consistent LLM judge using chain-of-thought prompting. Step-by-step guide with code for scoring and variance checks.
Calibrating LLM judges against human evaluation scores
A practical how-to for calibrating LLM judges against human scores: build a labeled set, fit a calibration layer, and measure agreement.
Building a rubric-based LLM judge prompt
Step-by-step guide to building a rubric-based LLM judge prompt for LLM-as-a-judge, with code examples and calibration against human labels.
More topics in developer tools
- CI/CD Pipelines for LLM Apps15
- LLM Evaluation Frameworks15
- Cost Optimization & Model Routing14
- Debugging Hallucinations & Output Quality14
- LangChain Debugging & Observability14
- LLM Observability Platforms14
- Migrating Between LLM Providers14
- Model Deprecation & Version Migration14
- RAG Pipeline Observability14
- Regression Testing for Prompts14
- Compliance & Audit Logging for Regulated Industries13
- CrewAI & AutoGen Multi-Agent Debugging13