| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - molecular-generation |
| - conditional-generation |
| - graph-tokenization |
| - chemistry |
| pretty_name: MOSAIC Conditional Motif Generation |
| --- |
| |
| # MOSAIC: Conditional Motif Generation |
|
|
| Conditional generation samples + metrics for the three MOSAIC tokenizers |
| (SENT, HDT-MC, HDTC) prompted with each of 6 shared ring/aromatic motifs, |
| across MOSES, GuacaMol, and COCONUT. |
|
|
| The conditioning prompt for each model is the standalone-motif tokenization, |
| with closing tokens stripped so the model continues from "the molecule starts |
| with this motif." For HDT-MC, the outer ENTER block is left open so the model |
| can add additional communities; for HDTC, the trailing super-graph block is |
| stripped so the model can add more typed communities. |
|
|
| ## Layout |
|
|
| - `{dataset}__AVG.png` — per-dataset metric table averaged over the 6 motifs |
| - `{dataset}__AVG__grid.png` — per-dataset 6×5 visual grid (one row per motif, |
| one column per model, plus reference + motif primer) |
| - `{dataset}/_reference/{motif}.txt` — k motif-containing reference SMILES drawn |
| from training (used as the comparison set for SNN / Frag / motif-distribution |
| MMDs) |
| - `{dataset}/{motif}/{dataset}__{motif}.png` — per-cell metric table |
| - `{dataset}/{motif}/{dataset}__{motif}__grid.png` — per-cell 5-column visual |
| grid (Reference | Motif Primer | SENT | HDT-MC | HDTC) |
| - `{dataset}/{motif}/{model}/generated_smiles.txt` — k=100 conditional generations |
| - `{dataset}/{motif}/{model}/generated_metadata.json` — gen-time stats (prompt |
| token sequence, decode rate, motif retention, sampling params, elapsed) |
| - `{dataset}/{motif}/{model}/metrics.json` — full computed metrics |
|
|
| ## Motifs |
|
|
| | Name | SMARTS / SMILES | |
| |------|-----------------| |
| | `benzene` | `c1ccccc1` | |
| | `pyridine` | `c1ccncc1` | |
| | `naphthalene` | `c1ccc2ccccc2c1` | |
| | `indole` | `c1ccc2[nH]ccc2c1` | |
| | `cyclohexane` | `C1CCCCC1` | |
| | `cyclopentane` | `C1CCCC1` | |
|
|
| ## Datasets |
|
|
| - **moses** — MOSES drug-like (training set ~1.6M) |
| - **guacamol** — GuacaMol drug-like (test split fallback, ~941 reference SMILES) |
| - **coconut** — COCONUT natural products (training set ~10K) |
|
|
| ## Models |
|
|
| Listed in the column order used by the rendered tables (flat → unsupervised |
| hierarchies → supervised hierarchy → typed hierarchy): |
|
|
| - **sent** — flat random-walk tokenizer (SENT) |
| - **hdt_lou** — HDT with Louvain community coarsening (HDT-Lou) |
| - **hdt_hac** — HDT with HAC-avg community coarsening (HDT-HAC) |
| - **hdt** — HDT with motif-community coarsening (HDT-MC) |
| - **hdtc** — HDT-Compositional, typed two-level (RING / FUNC / SINGLETON) |
|
|
| All models are gpt2xs (~11M params) trained with next-token prediction. |
| Per-cell sample budget: k=100 decodable molecules per (dataset, model, motif), |
| obtained via rejection sampling capped at 800 attempts. |
|
|
| ## Pipeline |
|
|
| Generation/metric/render code lives in the MOSAIC repo at |
| `scripts/conditional_motif/`. |
|
|
