ruvector/docs
ruvnet cfdcb8bb12 test(ac-3a): wire full-partition ARI — greedy beats Leiden, discovery #20
AC-3a now publishes full-partition ARI alongside the 2-way
coarsening. Measured on the default N=1024 SBM:

  2-way coarsened ARI (inherited, backward-compat):
    mincut  : -0.001    greedy  :  0.174
    louvain :  0.000    leiden  :  0.089

  **Full-partition ARI (new, correct metric):**
    greedy  full_ari :  **0.308**   ← surprising
    louvain full_ari :  0.000  (collapses)
    leiden  full_ari :  0.107
    cpm@γ=2.25       :  **0.425**   ← still best

**20th discovery: Leiden's aggregation+refinement actively HURTS
full-partition ARI vs greedy level-1 on this substrate.** Greedy
modularity (one pass of local moves, no aggregation) scores 0.308;
adding the aggregation + Traag refinement steps drops that to
0.107 — a 2.9× regression from the more sophisticated algorithm.
The refinement preserves well-connectedness (leiden_refinement.rs
tests still pass) but does so at the cost of merging structurally-
distinct communities from the level-1 output.

This flips the expected order: on hub-heavy SBMs, *more algorithm
is worse* when the objective is modularity and the target is
module recovery. CPM (item 17) was the right escape — non-
resolution-limited objective sidesteps the issue.

Final ranking on default SBM, full-partition ARI:
  CPM @ γ=2.25 : 0.425  (non-modularity objective)
  greedy L1    : 0.308  (minimal-algorithm modularity)
  Leiden       : 0.107  (maximal-algorithm modularity)
  Louvain      : 0.000  (aggregation collapses)

The pattern echoes item 11 (multi-level Louvain collapse on
hub-heavy SBMs) but at a finer granularity: item 11 said
'aggregation breaks', item 20 says 'even Leiden's refinement
can't fully repair it because the underlying modularity
objective has the resolution-limit issue'. The fix (item 17)
was a different objective, not a better algorithm.

Engineering implication: **for AC-3a on this substrate, level-1
greedy modularity is a stronger baseline than multi-level
Leiden.** The default Louvain / Leiden trajectory assumes
increasingly-sophisticated algorithms monotonically improve
module recovery; on hub-heavy SBMs that assumption is false,
and simpler-is-better up to the CPM break.

Files:
  - tests/acceptance_partition.rs: full_partition_ari helper,
    new eprintln publishing four full-ARI values against ground-
    truth module labels. No assertion change (ADR §14 threshold
    discipline: coarsening choices are decisions, not knobs).
  - docs/adr/ADR-154: §17 item 20 added with the surprising
    level-1 vs Leiden inversion and the 'more algorithm is
    worse' framing on this substrate.

All 95 prior tests unchanged.

Co-Authored-By: claude-flow <ruv@ruv.net>
EOF
)
2026-04-22 21:59:31 -04:00
..
adr test(ac-3a): wire full-partition ARI — greedy beats Leiden, discovery #20 2026-04-22 21:59:31 -04:00
analysis fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
api fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
benchmarks fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cloud-architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cnn feat(demo): add Self-Learning tab with 6 interactive training demos 2026-03-11 19:31:23 -04:00
code-reviews docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
dag docs(dag): add comprehensive Neural DAG Learning implementation plan 2025-12-29 22:15:55 +00:00
development feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
examples feat(musica): structure-first audio separation via dynamic mincut (#337) 2026-04-08 12:23:48 -05:00
gnn fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
guides docs: add missing capabilities to advanced features guide 2026-02-26 16:09:06 +00:00
hnsw fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
hooks feat(cli): Implement full hooks system in Rust CLI 2025-12-27 01:08:36 +00:00
implementation fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
integration fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
nervous-system docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
optimization fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
plans/subpolynomial-time-mincut chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
postgres fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
project-phases Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
publishing fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research feat(examples): connectome-fly SOTA example + ADR-154 2026-04-21 23:27:11 -04:00
reviews perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
ruvllm docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
rvagent feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
security feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
sparse-inference feat: Add PowerInfer-style sparse inference engine with precision lanes (#106) 2026-01-04 23:40:31 -05:00
sql feat(postgres): Add ruvector-postgres extension with SIMD optimizations (#42) 2025-12-02 09:55:07 -05:00
testing Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
training fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
.gitkeep Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
.nojekyll fix: add .nojekyll to disable Jekyll processing 2026-03-11 17:53:19 -04:00
agi-container.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C2-shell-execution-hardening.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C8_RESULT_VALIDATION_IMPLEMENTATION.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
consciousness-api.md feat(consciousness): SOTA IIT Φ, causal emergence, quantum collapse crate (ADR-131) 2026-03-31 16:36:25 -04:00
IMPLEMENTATION-C5.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
index.html refactor: move CNN demo to docs/cnn/ for shorter URL 2026-03-11 17:52:13 -04:00
INDEX.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
moe-routing-optimization-analysis.md perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
README.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
REPO_STRUCTURE.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research-openfang.md Add OpenFang project research document 2026-02-26 14:14:58 +00:00

RuVector Documentation

Complete documentation for RuVector, the high-performance Rust vector database with global scale capabilities.

📚 Documentation Structure

docs/
├── adr/                    # Architecture Decision Records
├── analysis/               # Research & analysis docs
├── api/                    # API references (Rust, Node.js, Cypher)
├── architecture/           # System design docs
├── benchmarks/             # Performance benchmarks & results
├── cloud-architecture/     # Cloud deployment guides
├── code-reviews/           # Code review documentation
├── dag/                    # DAG implementation
├── development/            # Developer guides
├── examples/               # SQL examples
├── gnn/                    # GNN/Graph implementation
├── guides/                 # User guides & tutorials
├── hnsw/                   # HNSW index documentation
├── hooks/                  # Hooks system documentation
├── implementation/         # Implementation details & summaries
├── integration/            # Integration guides
├── nervous-system/         # Nervous system architecture
├── optimization/           # Performance optimization guides
├── plans/                  # Implementation plans
├── postgres/               # PostgreSQL extension docs
├── project-phases/         # Development phases
├── publishing/             # NPM publishing guides
├── research/               # Research documentation
├── ruvllm/                 # RuVLLM documentation
├── security/               # Security audits & reports
├── sparse-inference/       # Sparse inference docs
├── sql/                    # SQL examples
├── testing/                # Testing documentation
└── training/               # Training & LoRA docs

Getting Started

Architecture & Design

API Reference

Performance & Benchmarks

Security

Implementation

Specialized Topics

Development

Research

  • research/ - Research documentation
    • cognitive-frontier/ - Cognitive frontier research
    • gnn-v2/ - GNN v2 research
    • latent-space/ - HNSW & attention research
    • mincut/ - MinCut algorithm research

For New Users

  1. Start with Getting Started Guide
  2. Try the Basic Tutorial
  3. Review API Documentation

For Cloud Deployment

  1. Read Architecture Overview
  2. Follow Deployment Guide
  3. Apply Performance Optimizations

For Contributors

  1. Read Contributing Guidelines
  2. Review Architecture Decisions
  3. Check Migration Guide

For Performance Tuning

  1. Review Optimization Guide
  2. Run Benchmarks
  3. Check Analysis

📊 Documentation Status

Category Directory Status
Getting Started guides/ Complete
Architecture architecture/, adr/ Complete
API Reference api/ Complete
Performance benchmarks/, optimization/, analysis/ Complete
Security security/ Complete
Implementation implementation/, integration/ Complete
Development development/, testing/ Complete
Research research/ 📚 Ongoing

Total Documentation: 460+ documents across 60+ directories


🔗 External Resources


Last Updated: 2026-02-26 | Version: 2.0.4 (core) / 0.1.100 (npm) | Status: Production Ready