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---
license: cc-by-4.0
pretty_name: MixtureVitae post-training evaluation records
tags:
- evaluation
- reproducibility
---
# MixtureVitae post-training evaluation records

The evaluation records behind the tables and figures of *Strong
Post-Training from Permissive, Reasoning-Enriched Pretraining*
(NeurIPS 2026), in one place. The pipeline
that turns them into the paper's tables, figures and quoted numbers is
[`permissive-post-train`](https://github.com/MixtureVitae/permissive-post-train). Its
`mv_post_train/inputs.json` pins every file here by SHA-256 and by a
revision of this repository, and `mvpt fetch-inputs` downloads them:

```bash
pip install -e . -r requirements-lock.txt
mvpt fetch-inputs        # every input of the paper, from here and its other sources
mvpt build --check       # rebuild every generated file and compare with results/
```

Some files are copies of public ones, and `inputs.json` keeps their original
sources as fallbacks: R13 and R13-language of
[`Ali-Elganzory/permissive-llms-artifacts`](https://github.com/Ali-Elganzory/permissive-llms-artifacts)
at commit `8cc2e51`, R14-scores and R14-ifeval of
[`laion/mv-posttrain-eval-responses`](https://huggingface.co/datasets/laion/mv-posttrain-eval-responses)
at revision `e820fb34` (R14), and S2-0.4b and S2-1.7b of the two checkpoints'
model repositories. The only other inputs of the paper are two small files in the
pipeline repository itself, its setup values and the Hugging Face records of
four checkpoints uploaded after S1 was taken. `docs/inputs.md` of the pipeline describes every
input.

## Files

The IDs are the pipeline's input IDs. Table and figure numbers are those of the
paper's revision of 2026-10-28, for O1 to O7 those of 2026-11-01, and for R25
to R29 those of 2026-11-06.

| ID | File | Size | SHA-256 | What it holds |
|---|---|---:|---|---|
| R13 | `protocol_a/canonical_reasoning_per_sample.csv` | 105 MB | `867ff6d6782b…` | The main Protocol A records: one score per checkpoint, seed, task and question, for 57 checkpoints. Tables 1, 14, 16 to 18, 20, 21, 38 (its decontaminated rows) and 42 (its rows without masking), Figures 2 to 4. |
| R15 | `protocol_a/comma_reasoning_unified_per_sample.csv` | 12 MB | `a8e33f163ce4…` | Protocol A records of the front-loaded Comma0.1 arm (six checkpoints). Tables 17, 18, 20 and 21, Figures 2 to 4. |
| R18 | `protocol_a/ablation_decontamination_0_4B_reasoning_per_sample.csv` | 61 MB | `021b81d039ec…` | Protocol A records of the 36 checkpoints of the 100B mixture ablation, the MV model without decontamination and the 0.4B comparison. Tables 35, 37, 38 (its rows without decontamination) and 40. |
| R19 | `protocol_a/masked_reasoning_per_sample.csv` | 9 MB | `8084115c57e8…` | Protocol A records of the four masked MV checkpoints (copies of the `laion/*-masked` models with the same weights). Table 42's rows with masking. |
| R20 | `protocol_a/fineweb_edu_16k_april_base_unified_per_sample.csv` | 2 MB | `153341e3f95a…` | Protocol A records of the FineWeb-Edu 16K base that its SFT and DPO models were trained from. Tables 1, 14, 17, 18, 20 and 21, Figures 2 to 4. |
| R21 | `protocol_a/ifeval_strict_per_sample_protocol_a.csv` | 34 MB | `eac0a09812bc…` | Protocol A IFEval verdicts with the strict checker, one row per checkpoint, seed and instruction, for 112 checkpoints. Every Protocol A IFEval score of the paper except DCLM-16K's, which R24 holds. |
| R22 | `protocol_a/phase1_livecodebenchv5_per_sample.csv` | 17 MB | `80b2d27da77a…` | Protocol A LiveCodeBench v5 verdicts, one row per checkpoint, seed and problem, for 112 checkpoints, on the 369 problems of LiveCodeBench v5 that Phase 2 runs. Every Protocol A LiveCodeBench score of the paper except DCLM-16K's, which R24 holds. |
| R24 | `protocol_a/dclm_16k_reasoning_evals_per_sample.csv` | 6 MB | `fcb6bd7b79f3…` | Protocol A records of the DCLM 16K checkpoints (base, Tulu3 SFT and DPO), with their IFEval verdicts and their LiveCodeBench v5 verdicts (task `LiveCodeBenchv5`) next to v2, because R21 and R22 do not cover them. DCLM's 16K rows of Tables 1 and 14. |
| R13-language | `language/ablation_frontloading_x_permissiveness_language_evaluations.csv` | 16 kB | `e108272f2227…` | One language score per task for the front-loading study's checkpoints without Comma0.1, and each task's shot count and metric. The shot counts and metrics of Table 13. The scores are a second source for most language cells of Tables 17 and 22, which print the runs of R8, R8-fineweb and R23. |
| R8 | `language/language_eval-logs.zip` | 2.9 GB | `0492e8a69dd6…` | LM Evaluation Harness results with per-question files and three prompt-example seeds, for 19 checkpoints of MV, Comma0.1 and Nemotron-CC-HQ. Tables 15, 17, 19, 22, 30 to 32, 39 and 43, and Figure 2's language panel. |
| R8-fineweb | `language/logs-fineweb.zip` | 2.0 GB | `d940f546b4dc…` | The same for 7 FineWeb-Edu checkpoints. Tables 15, 17, 19, 22, 30 and 31, and Figure 2's language panel. |
| R16 | `language/language_eval_all_models_2026-10-16.zip` | 3 MB | `bb0b7b1a2fc7…` | LM Evaluation Harness results for 82 checkpoints, one prompt-example seed, without per-question files. Tables 15, 30, 36, 39, 41 and 43. |
| R17 | `language/masked_models_lang_evals.zip` | 0.5 MB | `c53217be762c…` | LM Evaluation Harness results for five masked checkpoints. Table 43's rows with masking. |
| R23 | `language/language_eval_all_models_3seed_2026-10-26.zip` | 3.5 GB | `1a0422576760…` | LM Evaluation Harness results with per-question files and three prompt-example seeds (1234, 42 and 2025) for 24 checkpoints, run on 2026-10-26, and one-seed results files for 41 more, which are R16's. The front-loading study's language cells that R8 does not hold, and the intervals of its language contrasts: Tables 17, 19 and 22, and Figure 2's language panel. |
| R25 | `language/language_eval_dclm_16k_3seed_2026-10-27.zip` | 0.4 GB | `fb51da2a4fcb…` | LM Evaluation Harness results with per-question files and three prompt-example seeds (1234, 42 and 2025) for the DCLM 16K checkpoints (the 16K extension and its Tulu3 SFT and DPO models), in R23's layout without its outer folder. Table 18's DCLM-16k block. |
| R26 | `language/language_eval_nemotron16k_aug_3seed_2026-11-01.zip` | 0.3 GB | `4b059c419c5a…` | The same for the Tulu3 SFT and DPO models of Nemotron-CC-HQ's YaRN-extended 16K checkpoint, the ones the reasoning tables use. Table 18's Nemotron-16k block, with its 16K base from R23. |
| R14-scores | `phase2/eval_scores.parquet` | 70 kB | `666002c3c4e9…` | The three-seed Phase 2 scores of R14, with IFEval under all four definitions. Every Phase 2 result of the paper but those of R27's checkpoints. |
| R14-ifeval | `phase2/ifeval_allmetrics_persample.parquet` | 0.2 MB | `1dd7734ef79a…` | R14's IFEval counts per prompt and seed: instructions, and those followed with the strict and the loose checker. |
| R14-meta | `phase2/eval_responses_meta.parquet` | 2 MB | `59872f7e7a31…` | The small columns (model, stage, task, question, seed, correctness, checkpoint folder, token limit) of R14's answer file, `eval_responses.parquet` (10 GB), which is not copied here. `mvpt fetch-phase2-records` writes the same file from R14. |
| R27-scores | `phase2_jureca/eval_scores.parquet` | 11 kB | `521279ac8a39…` | The three-seed Phase 2 scores, in R14's format, of eight checkpoints evaluated under Protocol B on JURECA: the Tulu3 SFT checkpoint and the OpenThoughts3 30K run of Nemotron-CC-HQ's YaRN extension (Table 2's matched-compute Nemotron-CC-HQ), and the same two checkpoints of the enriched Nemotron-CC-HQ, Comma0.1 and FineWeb-Edu models (Table 2's enrichment block). The pipeline reads R14 and R27 together, and every Phase 2 table and number that uses these checkpoints comes from here. |
| R27-ifeval | `phase2_jureca/ifeval_allmetrics_persample.parquet` | 24 kB | `8c4a07f2073b…` | The same cells' IFEval counts per prompt and run, as R14-ifeval. |
| R27-meta | `phase2_jureca/eval_responses_meta.parquet` | 0.2 MB | `c8fe982f1af6…` | The small columns of the same cells' answer files, as R14-meta: question IDs and verdicts, no question or answer text. The answer files are not published, because they hold GPQA Diamond. |
| R27-lengths | `phase2_jureca/answer_lengths.parquet` | 0.6 MB | `b240516720da…` | One row per answer of the same cells, without its text, as R14-lengths. |
| R29 | `math500_rerun/per_question_n1.csv` | 4 MB | `c349e8a059a5…` | MATH500 evaluated again with a seed for each question (see below): one row per checkpoint, run and question, with the verdict and the answer's length in characters. One run of 100 sampled Phase 2 MATH500 cells, and three runs of the four checkpoints of the OT3 exclusion. Table 30's last column, §3.4 and Appendix E.2. |
| R14-lengths | `phase2/answer_lengths.parquet` | 6 MB | `9863758e52d1…` | One row per Phase 2 answer of R14, without its text: its length, and whether the grader found an answer and a code block. `mvpt measure-phase2-answers` writes the same file from R14 in about two hours. |
| S1 | `snapshots/hf_checkpoints.json` | 173 kB | `4d4723136230…` | A snapshot of the Hugging Face records of every checkpoint the paper evaluates (repos, weight hashes, model cards, training summaries, context settings), taken on 2026-10-12 and 2026-10-13 and updated on 2026-10-31 with the Phase 2 checkpoints uploaded on 2026-10-30 and HuggingFaceTB's SmolLM2-1.7B-Instruct-16k. It gives each checkpoint's parent in the results manifest. |
| S2-0.4b, S2-1.7b | `setup/*.config.json` | 1 kB each | `24a64d86ef89…`, `b2d8faeee3c6…` | The `config.json` of the 0.4B and 1.7B MV base models, the architectures of Table 5. |
| R6 | `older/logs_without_gpqa_items.zip` | 416 MB | `2f9db28c0e7a…` | LM Evaluation Harness and Evalchemy results files of the older evaluations, January to May 2026, without the GPQA Diamond items (see below). No table of the paper prints them, but the results manifest keeps them. |
| O1 | `overlap/excluded_items.csv` | 57 kB | `742229278d1a…` | The 1,720 benchmark items of 17 benchmarks that the audit of the training data identified, one row per benchmark and item ID. The comparisons without the identified items leave them out: Table 4 and Appendix A.3. |
| O2 | `overlap/overlap_sensitivity.csv` | 75 kB | `623541e0a3f2…` | Every comparison of Phase 2, Table 4, the front-loading study and the language suite, with all items and without O1's, each with its estimate, 95% interval and Benjamini-Hochberg q-value: 647 rows. Appendix A.3. |
| O3 | `overlap/found.parquet` | 1.5 MB | `e2536a6f4036…` | Where each item was found: the training dataset, its row and turn, the source within it, and the evidence (13-gram or exact). Appendix A.3's table of items found. |
| O4 | `overlap/mv_question_overlap_rates.csv` | 1 kB | `2b7b2b45460b…` | The share of the questions of the AceReason, Nemotron-Cascade and Superior-Reasoning 30K samples trained on that match MixtureVitae's pretraining reasoning data other than OpenThoughts3, by domain. Appendix E. |
| O5 | `overlap/mv_question_overlap_rates_ot3.csv` | 0.3 kB | `966ea7ba4e6b…` | The same for the Phase 2 OpenThoughts3 30K sample. Appendix E and §3.4. |
| O6 | `overlap/phase2_tokens.csv` | 1 kB | `e9d8658a7418…` | The training tokens of the four Phase 2 30K samples as trained: length per sample, the share cut at 16,384 tokens, and the supervised tokens. Appendix A.2. |
| O7 | `overlap/phase2_ot3_release.csv` | 0.4 kB | `94e064d554d3…` | The OpenThoughts3 30K sample as released, by domain: how many answers close their reasoning. Appendix A.2. |

The full SHA-256 of each file is in `inputs.json`, which checks every download.

## Formats

**Protocol A records** (R13, R15, R18 to R22, R24) have one row per checkpoint, decoding
seed, benchmark and question: `model_id, stage, model_group, front_loading,
context_length, seed, benchmark, sample_id, correct`, and in some files the
experiments the checkpoint belongs to. They hold no question or answer text.
Protocol A is greedy decoding with seeds 42, 1234 and 2025 (the paper's
Table 11).
**Language results** (R8, R8-fineweb, R16, R17, R23, R25, R26) are the results files
that the LM Evaluation Harness writes, zipped as received. R8, R8-fineweb and
R23, R25 and R26 also hold its per-question files, which contain the benchmark questions
and the models' answers. R23 keeps each checkpoint, task and seed in a folder
of its own (`<checkpoint>/<task>/seed<N>/<checkpoint>/`).
**Older evaluations** (R6) are the results files as received, except for
GPQA Diamond. GPQA asks that its items not be published in plain text, and
Evalchemy saves every item it scores with the results, so here each GPQA item
keeps only its GPQA record ID, the letter of the correct choice, and the model's
answer in each repetition if it is a letter (otherwise an empty string). The
scores and every other file are unchanged. `release/records/strip_gpqa.py` of
the pipeline writes this copy from the original.

The paths with `/e/scratch/jureap59/` in the results files are the working
directory of the cluster the evaluations ran on.

**Phase 2 records** (R14, R27) have one row per checkpoint, task and question
in R14-meta and R27-meta, with the run index (0, 1 and 2), the verdict and the
checkpoint folder. Protocol B samples at temperature 0.7 with three runs per
task (the paper's evaluation-settings table). R27's checkpoints were evaluated
on JURECA with the settings of R14 (YaRN factor 8 and 32,768 positions in the
evaluation copies), and the scripts as run are in the pipeline's
`docs/investigations/scripts/protocol_b_jureca/`.

**MATH500 reruns** (R29). The released Protocol B runs give every MATH500
question of run i the same sampling seed, so the answers of a run are
correlated. The reruns give question j of run i the seed
100000 + 500i + j, and otherwise keep Protocol B: temperature 0.7, 32,000 new
tokens, the chat template. Every run has 500 distinct seeds, and each answer is
graded with the LM Evaluation Harness's `is_equiv`. The pipeline's
`docs/investigations/math500_seed0.md` describes the runs, and
`docs/investigations/scripts/math500_seed0/` holds the patch to Evalchemy's
MATH500 task and the scripts that wrote this file.

**The benchmark-overlap audit** (O1 to O7) looked for the paper's benchmark
items in the training data with 13-gram and exact matching. Its files hold
item IDs, row numbers, dataset and shard names and counts, and no benchmark or
training text. The pipeline's `docs/inputs.md` describes each file, and
`mvpt render-overlap` turns them into the paper's Table 4, Appendix A.3 and the
overlap numbers of the text.

## License

The records are under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
The benchmark questions in R6, R8, R8-fineweb, R23, R25 and R26 keep the licenses of
their benchmarks, and the model answers in them those of the models that wrote
them.

## Versions

Records are added here as new runs and checkpoints are published. Each version
of the pipeline pins the revision it read, so a release of the paper's tables
always names the exact files behind it.

	---
	license: cc-by-4.0
	pretty_name: MixtureVitae post-training evaluation records
	tags:
	- evaluation
	- reproducibility
	---

	# MixtureVitae post-training evaluation records

	The evaluation records behind the tables and figures of *Strong
	Post-Training from Permissive, Reasoning-Enriched Pretraining*
	(NeurIPS 2026), in one place. The pipeline
	that turns them into the paper's tables, figures and quoted numbers is
	[`permissive-post-train`](https://github.com/MixtureVitae/permissive-post-train). Its
	`mv_post_train/inputs.json` pins every file here by SHA-256 and by a
	revision of this repository, and `mvpt fetch-inputs` downloads them:

	```bash
	pip install -e . -r requirements-lock.txt
	mvpt fetch-inputs # every input of the paper, from here and its other sources
	mvpt build --check # rebuild every generated file and compare with results/
	```

	Some files are copies of public ones, and `inputs.json` keeps their original
	sources as fallbacks: R13 and R13-language of
	[`Ali-Elganzory/permissive-llms-artifacts`](https://github.com/Ali-Elganzory/permissive-llms-artifacts)
	at commit `8cc2e51`, R14-scores and R14-ifeval of
	[`laion/mv-posttrain-eval-responses`](https://huggingface.co/datasets/laion/mv-posttrain-eval-responses)
	at revision `e820fb34` (R14), and S2-0.4b and S2-1.7b of the two checkpoints'
	model repositories. The only other inputs of the paper are two small files in the
	pipeline repository itself, its setup values and the Hugging Face records of
	four checkpoints uploaded after S1 was taken. `docs/inputs.md` of the pipeline describes every
	input.

	## Files

	The IDs are the pipeline's input IDs. Table and figure numbers are those of the
	paper's revision of 2026-10-28, for O1 to O7 those of 2026-11-01, and for R25
	to R29 those of 2026-11-06.

	\| ID \| File \| Size \| SHA-256 \| What it holds \|
	\|---\|---\|---:\|---\|---\|
	\| R13 \| `protocol_a/canonical_reasoning_per_sample.csv` \| 105 MB \| `867ff6d6782b…` \| The main Protocol A records: one score per checkpoint, seed, task and question, for 57 checkpoints. Tables 1, 14, 16 to 18, 20, 21, 38 (its decontaminated rows) and 42 (its rows without masking), Figures 2 to 4. \|
	\| R15 \| `protocol_a/comma_reasoning_unified_per_sample.csv` \| 12 MB \| `a8e33f163ce4…` \| Protocol A records of the front-loaded Comma0.1 arm (six checkpoints). Tables 17, 18, 20 and 21, Figures 2 to 4. \|
	\| R18 \| `protocol_a/ablation_decontamination_0_4B_reasoning_per_sample.csv` \| 61 MB \| `021b81d039ec…` \| Protocol A records of the 36 checkpoints of the 100B mixture ablation, the MV model without decontamination and the 0.4B comparison. Tables 35, 37, 38 (its rows without decontamination) and 40. \|
	\| R19 \| `protocol_a/masked_reasoning_per_sample.csv` \| 9 MB \| `8084115c57e8…` \| Protocol A records of the four masked MV checkpoints (copies of the `laion/*-masked` models with the same weights). Table 42's rows with masking. \|
	\| R20 \| `protocol_a/fineweb_edu_16k_april_base_unified_per_sample.csv` \| 2 MB \| `153341e3f95a…` \| Protocol A records of the FineWeb-Edu 16K base that its SFT and DPO models were trained from. Tables 1, 14, 17, 18, 20 and 21, Figures 2 to 4. \|
	\| R21 \| `protocol_a/ifeval_strict_per_sample_protocol_a.csv` \| 34 MB \| `eac0a09812bc…` \| Protocol A IFEval verdicts with the strict checker, one row per checkpoint, seed and instruction, for 112 checkpoints. Every Protocol A IFEval score of the paper except DCLM-16K's, which R24 holds. \|
	\| R22 \| `protocol_a/phase1_livecodebenchv5_per_sample.csv` \| 17 MB \| `80b2d27da77a…` \| Protocol A LiveCodeBench v5 verdicts, one row per checkpoint, seed and problem, for 112 checkpoints, on the 369 problems of LiveCodeBench v5 that Phase 2 runs. Every Protocol A LiveCodeBench score of the paper except DCLM-16K's, which R24 holds. \|
	\| R24 \| `protocol_a/dclm_16k_reasoning_evals_per_sample.csv` \| 6 MB \| `fcb6bd7b79f3…` \| Protocol A records of the DCLM 16K checkpoints (base, Tulu3 SFT and DPO), with their IFEval verdicts and their LiveCodeBench v5 verdicts (task `LiveCodeBenchv5`) next to v2, because R21 and R22 do not cover them. DCLM's 16K rows of Tables 1 and 14. \|
	\| R13-language \| `language/ablation_frontloading_x_permissiveness_language_evaluations.csv` \| 16 kB \| `e108272f2227…` \| One language score per task for the front-loading study's checkpoints without Comma0.1, and each task's shot count and metric. The shot counts and metrics of Table 13. The scores are a second source for most language cells of Tables 17 and 22, which print the runs of R8, R8-fineweb and R23. \|
	\| R8 \| `language/language_eval-logs.zip` \| 2.9 GB \| `0492e8a69dd6…` \| LM Evaluation Harness results with per-question files and three prompt-example seeds, for 19 checkpoints of MV, Comma0.1 and Nemotron-CC-HQ. Tables 15, 17, 19, 22, 30 to 32, 39 and 43, and Figure 2's language panel. \|
	\| R8-fineweb \| `language/logs-fineweb.zip` \| 2.0 GB \| `d940f546b4dc…` \| The same for 7 FineWeb-Edu checkpoints. Tables 15, 17, 19, 22, 30 and 31, and Figure 2's language panel. \|
	\| R16 \| `language/language_eval_all_models_2026-10-16.zip` \| 3 MB \| `bb0b7b1a2fc7…` \| LM Evaluation Harness results for 82 checkpoints, one prompt-example seed, without per-question files. Tables 15, 30, 36, 39, 41 and 43. \|
	\| R17 \| `language/masked_models_lang_evals.zip` \| 0.5 MB \| `c53217be762c…` \| LM Evaluation Harness results for five masked checkpoints. Table 43's rows with masking. \|
	\| R23 \| `language/language_eval_all_models_3seed_2026-10-26.zip` \| 3.5 GB \| `1a0422576760…` \| LM Evaluation Harness results with per-question files and three prompt-example seeds (1234, 42 and 2025) for 24 checkpoints, run on 2026-10-26, and one-seed results files for 41 more, which are R16's. The front-loading study's language cells that R8 does not hold, and the intervals of its language contrasts: Tables 17, 19 and 22, and Figure 2's language panel. \|
	\| R25 \| `language/language_eval_dclm_16k_3seed_2026-10-27.zip` \| 0.4 GB \| `fb51da2a4fcb…` \| LM Evaluation Harness results with per-question files and three prompt-example seeds (1234, 42 and 2025) for the DCLM 16K checkpoints (the 16K extension and its Tulu3 SFT and DPO models), in R23's layout without its outer folder. Table 18's DCLM-16k block. \|
	\| R26 \| `language/language_eval_nemotron16k_aug_3seed_2026-11-01.zip` \| 0.3 GB \| `4b059c419c5a…` \| The same for the Tulu3 SFT and DPO models of Nemotron-CC-HQ's YaRN-extended 16K checkpoint, the ones the reasoning tables use. Table 18's Nemotron-16k block, with its 16K base from R23. \|
	\| R14-scores \| `phase2/eval_scores.parquet` \| 70 kB \| `666002c3c4e9…` \| The three-seed Phase 2 scores of R14, with IFEval under all four definitions. Every Phase 2 result of the paper but those of R27's checkpoints. \|
	\| R14-ifeval \| `phase2/ifeval_allmetrics_persample.parquet` \| 0.2 MB \| `1dd7734ef79a…` \| R14's IFEval counts per prompt and seed: instructions, and those followed with the strict and the loose checker. \|
	\| R14-meta \| `phase2/eval_responses_meta.parquet` \| 2 MB \| `59872f7e7a31…` \| The small columns (model, stage, task, question, seed, correctness, checkpoint folder, token limit) of R14's answer file, `eval_responses.parquet` (10 GB), which is not copied here. `mvpt fetch-phase2-records` writes the same file from R14. \|
	\| R27-scores \| `phase2_jureca/eval_scores.parquet` \| 11 kB \| `521279ac8a39…` \| The three-seed Phase 2 scores, in R14's format, of eight checkpoints evaluated under Protocol B on JURECA: the Tulu3 SFT checkpoint and the OpenThoughts3 30K run of Nemotron-CC-HQ's YaRN extension (Table 2's matched-compute Nemotron-CC-HQ), and the same two checkpoints of the enriched Nemotron-CC-HQ, Comma0.1 and FineWeb-Edu models (Table 2's enrichment block). The pipeline reads R14 and R27 together, and every Phase 2 table and number that uses these checkpoints comes from here. \|
	\| R27-ifeval \| `phase2_jureca/ifeval_allmetrics_persample.parquet` \| 24 kB \| `8c4a07f2073b…` \| The same cells' IFEval counts per prompt and run, as R14-ifeval. \|
	\| R27-meta \| `phase2_jureca/eval_responses_meta.parquet` \| 0.2 MB \| `c8fe982f1af6…` \| The small columns of the same cells' answer files, as R14-meta: question IDs and verdicts, no question or answer text. The answer files are not published, because they hold GPQA Diamond. \|
	\| R27-lengths \| `phase2_jureca/answer_lengths.parquet` \| 0.6 MB \| `b240516720da…` \| One row per answer of the same cells, without its text, as R14-lengths. \|
	\| R29 \| `math500_rerun/per_question_n1.csv` \| 4 MB \| `c349e8a059a5…` \| MATH500 evaluated again with a seed for each question (see below): one row per checkpoint, run and question, with the verdict and the answer's length in characters. One run of 100 sampled Phase 2 MATH500 cells, and three runs of the four checkpoints of the OT3 exclusion. Table 30's last column, §3.4 and Appendix E.2. \|
	\| R14-lengths \| `phase2/answer_lengths.parquet` \| 6 MB \| `9863758e52d1…` \| One row per Phase 2 answer of R14, without its text: its length, and whether the grader found an answer and a code block. `mvpt measure-phase2-answers` writes the same file from R14 in about two hours. \|
	\| S1 \| `snapshots/hf_checkpoints.json` \| 173 kB \| `4d4723136230…` \| A snapshot of the Hugging Face records of every checkpoint the paper evaluates (repos, weight hashes, model cards, training summaries, context settings), taken on 2026-10-12 and 2026-10-13 and updated on 2026-10-31 with the Phase 2 checkpoints uploaded on 2026-10-30 and HuggingFaceTB's SmolLM2-1.7B-Instruct-16k. It gives each checkpoint's parent in the results manifest. \|
	\| S2-0.4b, S2-1.7b \| `setup/*.config.json` \| 1 kB each \| `24a64d86ef89…`, `b2d8faeee3c6…` \| The `config.json` of the 0.4B and 1.7B MV base models, the architectures of Table 5. \|
	\| R6 \| `older/logs_without_gpqa_items.zip` \| 416 MB \| `2f9db28c0e7a…` \| LM Evaluation Harness and Evalchemy results files of the older evaluations, January to May 2026, without the GPQA Diamond items (see below). No table of the paper prints them, but the results manifest keeps them. \|
	\| O1 \| `overlap/excluded_items.csv` \| 57 kB \| `742229278d1a…` \| The 1,720 benchmark items of 17 benchmarks that the audit of the training data identified, one row per benchmark and item ID. The comparisons without the identified items leave them out: Table 4 and Appendix A.3. \|
	\| O2 \| `overlap/overlap_sensitivity.csv` \| 75 kB \| `623541e0a3f2…` \| Every comparison of Phase 2, Table 4, the front-loading study and the language suite, with all items and without O1's, each with its estimate, 95% interval and Benjamini-Hochberg q-value: 647 rows. Appendix A.3. \|
	\| O3 \| `overlap/found.parquet` \| 1.5 MB \| `e2536a6f4036…` \| Where each item was found: the training dataset, its row and turn, the source within it, and the evidence (13-gram or exact). Appendix A.3's table of items found. \|
	\| O4 \| `overlap/mv_question_overlap_rates.csv` \| 1 kB \| `2b7b2b45460b…` \| The share of the questions of the AceReason, Nemotron-Cascade and Superior-Reasoning 30K samples trained on that match MixtureVitae's pretraining reasoning data other than OpenThoughts3, by domain. Appendix E. \|
	\| O5 \| `overlap/mv_question_overlap_rates_ot3.csv` \| 0.3 kB \| `966ea7ba4e6b…` \| The same for the Phase 2 OpenThoughts3 30K sample. Appendix E and §3.4. \|
	\| O6 \| `overlap/phase2_tokens.csv` \| 1 kB \| `e9d8658a7418…` \| The training tokens of the four Phase 2 30K samples as trained: length per sample, the share cut at 16,384 tokens, and the supervised tokens. Appendix A.2. \|
	\| O7 \| `overlap/phase2_ot3_release.csv` \| 0.4 kB \| `94e064d554d3…` \| The OpenThoughts3 30K sample as released, by domain: how many answers close their reasoning. Appendix A.2. \|

	The full SHA-256 of each file is in `inputs.json`, which checks every download.

	## Formats

	Protocol A records (R13, R15, R18 to R22, R24) have one row per checkpoint, decoding
	seed, benchmark and question: `model_id, stage, model_group, front_loading,
	context_length, seed, benchmark, sample_id, correct`, and in some files the
	experiments the checkpoint belongs to. They hold no question or answer text.
	Protocol A is greedy decoding with seeds 42, 1234 and 2025 (the paper's
	Table 11).

	Language results (R8, R8-fineweb, R16, R17, R23, R25, R26) are the results files
	that the LM Evaluation Harness writes, zipped as received. R8, R8-fineweb and
	R23, R25 and R26 also hold its per-question files, which contain the benchmark questions
	and the models' answers. R23 keeps each checkpoint, task and seed in a folder
	of its own (`<checkpoint>/<task>/seed<N>/<checkpoint>/`).

	Older evaluations (R6) are the results files as received, except for
	GPQA Diamond. GPQA asks that its items not be published in plain text, and
	Evalchemy saves every item it scores with the results, so here each GPQA item
	keeps only its GPQA record ID, the letter of the correct choice, and the model's
	answer in each repetition if it is a letter (otherwise an empty string). The
	scores and every other file are unchanged. `release/records/strip_gpqa.py` of
	the pipeline writes this copy from the original.

	The paths with `/e/scratch/jureap59/` in the results files are the working
	directory of the cluster the evaluations ran on.

	Phase 2 records (R14, R27) have one row per checkpoint, task and question
	in R14-meta and R27-meta, with the run index (0, 1 and 2), the verdict and the
	checkpoint folder. Protocol B samples at temperature 0.7 with three runs per
	task (the paper's evaluation-settings table). R27's checkpoints were evaluated
	on JURECA with the settings of R14 (YaRN factor 8 and 32,768 positions in the
	evaluation copies), and the scripts as run are in the pipeline's
	`docs/investigations/scripts/protocol_b_jureca/`.

	MATH500 reruns (R29). The released Protocol B runs give every MATH500
	question of run i the same sampling seed, so the answers of a run are
	correlated. The reruns give question j of run i the seed
	100000 + 500i + j, and otherwise keep Protocol B: temperature 0.7, 32,000 new
	tokens, the chat template. Every run has 500 distinct seeds, and each answer is
	graded with the LM Evaluation Harness's `is_equiv`. The pipeline's
	`docs/investigations/math500_seed0.md` describes the runs, and
	`docs/investigations/scripts/math500_seed0/` holds the patch to Evalchemy's
	MATH500 task and the scripts that wrote this file.

	The benchmark-overlap audit (O1 to O7) looked for the paper's benchmark
	items in the training data with 13-gram and exact matching. Its files hold
	item IDs, row numbers, dataset and shard names and counts, and no benchmark or
	training text. The pipeline's `docs/inputs.md` describes each file, and
	`mvpt render-overlap` turns them into the paper's Table 4, Appendix A.3 and the
	overlap numbers of the text.

	## License

	The records are under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
	The benchmark questions in R6, R8, R8-fineweb, R23, R25 and R26 keep the licenses of
	their benchmarks, and the model answers in them those of the models that wrote
	them.

	## Versions

	Records are added here as new runs and checkpoints are published. Each version
	of the pipeline pins the revision it read, so a release of the paper's tables
	always names the exact files behind it.