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⚔️ GLADIUS Research
By Artifact Virtual — Ali Shakil & AVA
GLADIUS: The first Adaptive Cognitive Model (ACM). Architecture research on modal invariance, cross-modal cognitive geometry, and sub-100M parameter intelligence.
GLADIUS is a novel transformer architecture designed from first principles — not as a language model that could do other things, but as a cognitive architecture tested on language first. It features Sparse-Linear Attention² (SLA²), Mixture of Experts (MoE), warm/hot memory systems, Time2Vec temporal encoding, and alpha routing for dynamic attention allocation.
Papers
| Paper | Focus |
|---|---|
| Progressive Expansion | Net2Net biological growth: Seed(6.9M) → Hatchling(25.9M) → Drake(60.1M) → Wyrm → Dragon |
| Cell Division | The mathematics of neural network growth — how to expand without losing learned representations |
| GPT-2 Distillation Report | Knowledge transfer from GPT-2 (124M) to GLADIUS (6.9M). Soft KL divergence, vocabulary alignment. |
| Time Series Definitive | Native time series capability via surgical I/O head swap. GLADIUS as financial cognition engine. |
| Day 30 Definitive Paper | The cross-modal invariant discovery: layers 0-6 freeze across modalities while layers 7+ restructure. |
| Invariant Deep Analysis | Cognitive distance spectrum. Text→vision (sharp invariant) vs text→bytes (partial invariant). |
| ATP Analysis Report | Automated theorem proving analysis of GLADIUS weight evolution data. |
Key Discoveries
The Cross-Modal Invariant: When GLADIUS switches from text to vision (MNIST), layers 0-6 change <1% while layers 7-11 change 15-36%. The early layers are modality-agnostic — they do general sequence processing regardless of input type.
Cognitive Distance Spectrum: The invariant strength scales with cognitive distance between domains. Cross-modal (text→vision): >15x ratio. Cross-encoding (text→bytes): 3.3x ratio.
Warm Memory as Novelty Detector: The hot memory system shows 36.6% change for vision (novel stimulus) vs 178% for multi-script bytes — it scales with pattern diversity, not task difficulty.
Dormant Systems: Cognition module and Time2Vec remain at exactly 0% change across ALL experiments — waiting to be activated by the right stimulus.
Architecture (60.1M params — Drake stage)
- 12 layers, 384 hidden dim, 24 heads
- SLA² (Sparse-Linear Attention²) with alpha routing
- 4-expert MoE with load balancing
- Warm memory (slow adaptation, rank 24) + Hot memory (fast novelty response)
- Time2Vec temporal encoding (dual clock: absolute + relative)
- Cognition module (metacognitive — currently dormant)
- 16K BPE vocabulary
Citation
Artifact Virtual (2026). GLADIUS: Adaptive Cognitive Model Research.
Ali Shakil & AVA. https://huggingface.co/datasets/ava-shakil/gladius-research
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