{
  "date": "2026-10-01",
  "model": "d0rj/diffusion-51M-base",
  "protocol": "Full selected splits; lm-eval 0.4.12; seed 1234; BF16 on RTX 5070 Ti;\ncontext cap 2048 (ArithMark 1024), TF32 disabled, no chat template and no added\nfew-shot examples. TruthfulQA retains the harness's fixed six-QA preamble.\nArithMark and BananaMind normalize by continuation token count; ordinary harness\nacc_norm uses its own length normalization. BananaMind is raw accuracy, not Elo.\nSciQ includes the support passage. Balanced COPA uses the mirrored 1000-item\ntrain-named evaluation split; cRia's split was inferred, not confirmed.\nMMLU scores full answer continuations across 57 subjects, weighted by item count;\nBLiMP averages 67 equal-sized minimal-pair subsets. Standard errors are retained\nfrom each evaluator. Wilson intervals are reported only where the runner logged\nbinary item accuracy; MC2 is probability mass, not binary accuracy. These\nintervals do not model dependence between paired/templated examples or training\nseed variation. UL2, PrefixLM and experimental diffusion PLL use their documented\nconditional scoring protocols; PLL exposes the other answer tokens and is not\nautoregressive likelihood. cRia's published scores used a different precision\nand benchmark-adapted checkpoint; this completes our comparison coverage, not\nan independent reproduction of cRia or an official leaderboard submission.",
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    "tb": "runs/diffusion-gpu-v2/tb",
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