3D Difficulty Manifolds
Navigate reasoning landscapes as interactive 3D terrain. Explore how model performance varies across multiple difficulty dimensions simultaneously with enhanced surface analysis.
Token-Frequency Analysis
Apply FFT to tokenized reasoning problems, revealing spectral signatures and validating difficulty parameters through frequency domain analysis of cognitive architectures.
Six Cognitive Domains
Evaluate across arithmetic, boolean logic, object tracking, sequence manipulation, temporal reasoning, and pattern recognition for comprehensive cognitive assessment.
Parametric Test Generation
Generate infinite unique test instances within controlled difficulty manifolds. Eliminate contamination through deterministic coordinate-based seeding and hierarchical sampling.
Statistical Rigor
Excess accuracy correction, truncation handling, and dynamic confidence intervals with Winston methodology ensure meaningful model and task comparisons.
Progressive Evaluation
Hierarchical multi-degree system enables rapid model exploration (Degree 0) scaling through standard assessment (Degree 1) to research-grade precision (Degree 2).
ReasonScape: Information Processing Evaluation for Large Language Models
ReasonScape introduces a next-generation evaluation methodology that treats language models as analyzable information processing systems. Through parametric test generation, spectral analysis, and interactive visualization, ReasonScape reveals cognitive architecture patterns invisible to traditional benchmarks. The M6 suite provides comprehensive assessment across six cognitive domains with progressive difficulty degrees, enabling both rapid model comparison and research-grade analysis.