Core Architecture
Core Judging Architecture
Hierarchical Model Evaluation
Primary Judge Models:
400B parameter LLaMA-4: Primary evaluation model for complex reasoning tasks
700B parameter DeepSeek: Specialized evaluation for domain-specific content
Ensemble judging: Multiple LRMs provide consensus-based evaluation scores
Specialized Judge Models:
2.8B parameter models: Fast evaluation for simple quality checks
Nano models (4.1B): Optimized evaluators for specific domains
Domain-specific judges: Fine-tuned models for medical, legal, technical content
Reference-Free Evaluation System
Evaluation Tracking Infrastructure:
873+ feedback items in current evaluation dataset
Real-time quality scoring without requiring golden standard datasets
10-second interval processing for systematic evaluation collection
Automated data cleaning removing ~109 invalid entries during processing
Quality Assessment Dimensions:
5-star evaluation datasets for high-quality content analysis
1-star evaluation datasets for failure mode identification
Comparative scoring between different model outputs
Auto-optimization algorithms for continuous score improvement
Content Quality Assessment:
Factual accuracy evaluation using knowledge validation
Logical consistency checking for reasoning chains
Completeness assessment for comprehensive responses
Relevance scoring for context appropriateness
Style and Presentation Evaluation:
Clarity and readability assessment for user experience
Professional tone evaluation for business contexts
Technical accuracy for specialized domain content
User intent alignment for goal achievement assessment
Evaluation Methodologies
Consensus-Based Judging
Multi-Judge Ensemble:
Independent evaluation by multiple judge models
Consensus scoring using weighted voting mechanisms
Disagreement analysis for identifying edge cases
Confidence-weighted aggregation for reliable final scores
Judge Model Specialization:
Domain experts: Medical, legal, technical, creative content judges
Task specialists: Summarization, translation, reasoning, generation judges
Quality dimensions: Accuracy, clarity, completeness, relevance judges
User perspective: Different demographic and use-case specific judges
Comparative Evaluation Framework
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