- Tensor Parser Network converts standard tensors to human-readable text
- Not a runtime component; purely a training/debugging/verification tool
- Dedicated parsers for each tensor type (ref, memory, reasoning, expression, control)
- Three data generation methods: from subnet training, synthetic via LLM, end-to-end collection
- MVP approach: rule-based template parser (zero training, usable immediately)
- Iterative roadmap: rules → learned parsers → unified LLM-based generator
- Training dataset construction, evaluation metrics, and usage scenarios