refresh model card: E0+E1 complete, held-out eval results

README.md

@@ -274,3 +274,39 @@ FlashInfer is disabled (it misdetects sm_120); Liger is disabled because it supp
 
 Apache-2.0, matching the `Qwen/Qwen3-4B-Instruct-2507` base model. The prompt splits derive from a
 public writing-prompts corpus; stories in `outputs/pool_4b/` are model generations.
+
+
+## Status (updated — E0 and E1 both complete, 300 steps each)
+
+| arm | status | result |
+|---|---|---|
+| **E0** quality-only GRPO | ✅ complete, 300 steps | quality +0.303, diversity flat |
+| **E1** + pairwise deviation | ✅ complete, 300 steps | **diversity 5–6× E0's gain**, quality +0.243 |
+| E2 div-grpo-group (log-det marginal) | ⏸ stopped at step 4, config ready | — |
+| E3 multi-positive weighted DPO | ⏸ pairs built (3593 rows), not trained | — |
+| E4a/E4b DivPO emb/prob | ⏸ pairs built (956 rows each), not trained | — |
+
+### Held-out evaluation (30 prompts × 16 samples = 480 stories/model)
+
+| model | quality | eff_rank (of 16) | pairwise | logdet | distinct-4 | self-BLEU |
+|---|---|---|---|---|---|---|
+| base | 6.472 | 1.891 | 0.1179 | −32.46 | 0.9378 | 0.2875 |
+| E0 quality-only | 6.716 | 1.957 | 0.1259 | −31.59 | 0.9485 | 0.2635 |
+| **E1 +deviation** | **6.864** | **2.081** | **0.1390** | **−30.08** | 0.9464 | 0.2625 |
+
+**E1 wins on both axes:** vs base it gains 2.9× E0's effective-rank improvement
+*and* 1.6× E0's quality improvement. Not a diversity-for-quality trade.
+
+**Key methodological finding:** embedding metrics separate the arms by 2.9×;
+n-gram metrics (distinct-4, self-BLEU) do not separate them at all — distinct-4
+actually rates E0 *higher*. The collapse is tonal/structural, not lexical.
+
+**Key finding on LLM judges:** across 15,870 scored stories,
+`corr(judge "novelty", a story's actual embedding deviation) = +0.057`, while
+`corr(judge "novelty", judge quality) = +0.799`. An LLM judge's novelty score is
+~80% a restatement of quality and carries almost no information about semantic
+distinctiveness.
+
+See **`REPORT.pdf`** for the full write-up (metrics, figures, story examples,
+qualitative read) and **`NOTES.md`** for the complete engineering log including
+every bug and every retracted claim.