| --- |
| language: en |
| license: mit |
| tags: |
| - diffusion |
| - text-generation |
| - riddles |
| - diffusion-lm |
| datasets: |
| - prajwaldongre/riddles-a-synthetic-riddle-dataset-for-nlp |
| metrics: |
| - exact-match |
| - token-f1 |
| --- |
| |
| # Diffusion-LM Riddle Solver — Phase 3 Reconstructed |
|
|
| A Diffusion-LM-style (Li et al., 2022) text generation model trained on 232 synthetic riddles. Held-out exact match: **47.0%** (K=1 and K=10). |
|
|
| ## Model description |
|
|
| Continuous embedding diffusion with a Transformer encoder/decoder. The model takes a riddle as context and iteratively denoises Gaussian noise into answer word embeddings via a learned reverse process. |
|
|
| ## Intended use |
|
|
| Research and diagnostics. Not a production-ready riddle solver. |
|
|
| ## Training data |
|
|
| [Riddles — A Synthetic Riddle Dataset for NLP](https://www.kaggle.com/datasets/prajwaldongre/riddles-a-synthetic-riddle-dataset-for-nlp) (CC0). 232 training examples after deduplication. |
|
|
| ## Architecture |
|
|
| | Parameter | Value | |
| |-----------|-------| |
| | Parameters | 8,024,576 | |
| | Timesteps (T) | 200 | |
| | d_model | 256 | |
| | Layers | 4 | |
| | d_ff | 1024 | |
| | Heads | 4 | |
| | Answer length | 4 | |
| | Noise schedule | sqrt power-law | |
|
|
| ## Performance |
|
|
| | Split | Exact match (K=1) | Token F1 | |
| |-------|-------------------|----------| |
| | Train (n=192) | 87.5% | 0.960 | |
| | Held-out (n=66) | 47.0% | 0.523 | |
|
|
| ## Limitations |
|
|
| - Trained on 232 examples only. Does not generalize broadly. |
| - Uses continuous embedding diffusion with Euclidean clamping. Discrete formulations may differ. |
| - Exact-match metric penalizes semantically equivalent answers. |
|
|
| ## Files |
|
|
| - `model.safetensors`: Model weights |
| - `config.json`: Architecture hyperparameters |
| - `vocab.json`: Vocabulary mapping |
| - `inference.py`: Standalone prediction script |
|
|
| ## Source |
|
|
| Full source code, diagnostics, and reproduction configs: [github.com/beme08/riddle-diffusion-lm](https://github.com/beme08/riddle-diffusion-lm) |
|
|
