TinyFabulist

TinyFabulist is a three-stage research program built around controlled synthetic narratives.

TF1 — generation

Structured six-slot specifications are expanded into prompts and passed to open-weight generators no larger than 8B parameters. The released artifact is a three-million-story English corpus with generation metadata and evaluation signals.

TF2 — English–Romanian translation

TF2 turns selected TF1 stories into English–Romanian parallel resources and tests how far a fine-tuned open model can narrow the gap to much larger systems at lower inference cost. The project separates the 15K reference set, the three-million-pair corpus, and the released model; they serve different purposes.

TF3 — compact Romanian models

TF3 covers tokenizer construction, from-scratch pre-training, compression, evaluation, and Romanian-native generation. The current paper distinguishes the 51.65M-parameter model from the 26.45M-parameter compressed student; neither number should be reduced to “a 50M model” without context.

Evaluation and Romanian NLP

Two supporting lines of work cut across the pipeline:

  • a survey of synthetic text and code generation (arXiv);
  • Romanian diacritic restoration, including the InnoComp 2025 study published in Springer CCIS 2794 (paper, preprint).

The open-weight judge-panel work remains a research question, not a settled replacement for human or proprietary evaluation. The design notes on this site therefore distinguish validation plans from measured agreement.

Reproducibility

Public papers, datasets, prompts, and code improve auditability. They do not make hardware behavior, third-party model serving, or stochastic execution automatically identical. Each technical note records the boundary it actually tested.