Datasets:
Add dataset card and build metadata
Browse files- README.md +136 -0
- summary.json +72 -0
- thinking-audit.json +31 -0
- train-shards.json +41 -0
README.md
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| 1 |
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---
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| 2 |
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license: apache-2.0
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| 3 |
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task_categories:
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| 4 |
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- text-generation
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| 5 |
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language:
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- en
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| 7 |
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tags:
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| 8 |
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- dpo
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| 9 |
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- preference
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| 10 |
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- swe-agent
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- code
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| 12 |
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- reasoning
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size_categories:
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- 10K<n<100K
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---
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| 16 |
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# Gen Vinhable — King vs challenger preference pairs
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| 18 |
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| 19 |
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Preference data for DPO on multi-turn software-engineering agent trajectories from the Albedo
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| 20 |
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subnet (Bittensor SN97). Each pair compares two rollouts of the **same** sample in the **same**
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evaluation run: one by the reigning King model and one by the challenger it was evaluated against.
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Both sides are Qwen3.6-35B-A3B fine-tunes generated by production with thinking enabled, and both
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were scored by the same judge on the same checklist. The label is simply which rollout scored
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higher. Unlike a teacher-vs-model dataset, the two sides therefore think in the same way, so the
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presence or absence of reasoning cannot become a shortcut for the preference.
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## Layout
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| 30 |
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| File | Samples | Pairs |
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| 31 |
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|---|---:|---:|
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| `train-00000-of-00005.jsonl` | 9,314 | 1,570 |
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| 33 |
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| `train-00001-of-00005.jsonl` | 10,188 | 1,714 |
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| `train-00002-of-00005.jsonl` | 11,997 | 2,012 |
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| `train-00003-of-00005.jsonl` | 17,205 | 2,873 |
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| `train-00004-of-00005.jsonl` | 17,335 | 2,893 |
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| `dev.jsonl` | 7,083 | 1,188 |
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| **Total** | **73,122** | **12,250** |
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Train and dev are disjoint by `task_group`. All samples of a pair live in the same file.
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Evaluation runs finished between 2026-09-04 and 2026-09-23 and were taken newest first, so the
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newest Kings dominate:
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| 44 |
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| 45 |
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| King version | Pairs |
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| 46 |
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|---|---:|
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| 47 |
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| 127 | 2,636 |
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| 48 |
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| 126 | 2,609 |
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| 49 |
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| 125 | 2,679 |
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| 50 |
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| 124 | 1,693 |
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| 51 |
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| 123 | 1,706 |
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| 52 |
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| 122 | 927 |
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| 53 |
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| 54 |
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Preferences: King 6,236, challenger
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| 55 |
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5,769, tie 245
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| 56 |
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(2% of pairs).
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| 57 |
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| 58 |
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## Pair selection
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| 59 |
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| 60 |
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Every sample has two King rollouts and two challenger rollouts, so four King-vs-challenger
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| 61 |
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pairings. A pairing is eligible when:
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| 62 |
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| 63 |
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* both rollouts were scored;
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| 64 |
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* each side has at least four assistant turns, split into the same number (4-6) of behaviour groups;
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| 65 |
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* the first behaviour group matches on both sides;
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| 66 |
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* the winner is not flagged for amputated thinking (a rejected rollout may be).
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| 67 |
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| 68 |
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Of the eligible pairings, the one with the **largest score gap** is kept. One side is always the
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| 69 |
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King and the other always the challenger. Each exact context appears once, from its newest run.
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| 70 |
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Tasks used in the authors' local evaluation batch are excluded.
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| 71 |
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| 72 |
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## Row schema
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| 73 |
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| 74 |
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| Field | Meaning |
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| 75 |
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|---|---|
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| 76 |
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| `pair_id`, `sample_uid` | pair id; `sample_uid` is `pair_id#k<prefix_groups>` |
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| 77 |
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| `prompt` | shared prefix, every message `loss: false` |
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| 78 |
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| `chosen`, `rejected` | the two continuations |
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| 79 |
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| `preference` | `king`, `challenger` or `tie` |
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| 80 |
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| `chosen_side`, `rejected_side` | which model produced each side |
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| 81 |
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| `chosen_rollout`, `rejected_rollout` | rollout ids (`#r1` / `#r2`) in the source run |
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| 82 |
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| `king_score`, `challenger_score`, `margin` | production scores of the two rollouts and their gap |
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| 83 |
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| `rejected_amputated_thinking` | the rejected rollout was flagged for amputated thinking |
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| 84 |
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| `eligible_pairings` | how many of the four pairings passed the filters |
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| 85 |
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| `prefix_groups`, `group_count`, `is_full_trajectory` | turn-split position |
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| 86 |
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| `chosen_behavior_sequence`, `rejected_behavior_sequence` | per-group behaviour labels |
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| 87 |
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| `eval_run_id`, `finished_at`, `king_version`, `challenger_uid` | provenance of the run |
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| 88 |
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| `split`, `sample_id`, `task_group`, `source`, `sample_phase`, `question_mode`, `scoring_mode` | provenance of the sample |
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| 89 |
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| 90 |
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## Loss contract
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| 91 |
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| 92 |
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Within a sample, `loss: true` marks **only the assistant turns of the final behaviour group**. The
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| 93 |
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prompt, environment observations and earlier groups are unsupervised context, so across the
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`k = 1..K` samples of a pair each assistant turn is a target exactly once. Harness-written turns
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(`harness_text: true`, a truncation notice) and empty turns are never supervised.
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## Thinking contract — read before training
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Assistant `content` is the **exact text the model generated** after production's generation prompt
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| 100 |
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`<|im_start|>assistant\n<think>\n`: its reasoning, `</think>`, then the action. Render every
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| 101 |
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completion turn verbatim:
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```
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<|im_start|>assistant\n<think>\n + content + <|im_end|>
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```
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| 107 |
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Do **not** pass these turns through the chat template. About a quarter of production turns never
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| 108 |
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close the think block (`think_closed: false`); the template would re-render them with an empty
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| 109 |
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`<think>\n\n</think>` in front, which is exactly the fingerprint Albedo penalises (a rollout where
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| 110 |
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most turns open with an empty `</think>` has its score halved). The prompt is ordinary chat history
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| 111 |
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and can go through the template.
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| 113 |
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Audit of the released data (genesis tokenizer):
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| 114 |
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| 115 |
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| | chosen | rejected |
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| 116 |
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|---|---:|---:|
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| 117 |
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| turns that close the think block | 70.1% | 71.0% |
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| 118 |
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| turns opening with an empty `</think>` | 0.00% | 0.00% |
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| 119 |
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| median reasoning length (chars) | 516.0 | 443 |
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| 120 |
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| 121 |
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The supervised span starts on a token boundary after `<think>\n`, and `</think>` inside content
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| 122 |
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encodes as its single special token.
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| 124 |
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## Turn splitting
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| 125 |
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| 126 |
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A pair yields one sample per prefix length `k`: `chosen` is the first `k` behaviour groups of the
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| 127 |
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winning rollout and `rejected` the first `k` of the losing one, against the same prompt. From
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| 128 |
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`k >= 2` each side carries its own earlier groups as context, so the objective is a contrastive
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| 129 |
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variant of DPO rather than the textbook derivation. Filter to `is_full_trajectory == true` for one
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plain trajectory-level pair per sample.
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## Caveats
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| 133 |
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* Labels come from production's three-vote binary checklist judge. Small gaps are noisy.
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* Kings and challengers are closely related models, so many pairs differ in a few turns only.
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* Observations were produced by Albedo's LLM environment simulator, not by executing code.
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summary.json
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| 1 |
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{
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| 2 |
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"schema": "albedo-gen-dpo-summary-v1",
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| 3 |
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"counts": {
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| 4 |
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"pairing_rejected:fewer_than_four_turns": 78,
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| 5 |
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"pairing_rejected:first_group_mismatch": 2433,
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| 6 |
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"pairs:dev": 1188,
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| 7 |
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"pairs:king_version:122": 927,
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| 8 |
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"pairs:king_version:123": 1706,
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| 9 |
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"pairs:king_version:124": 1693,
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| 10 |
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"pairs:king_version:125": 2679,
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| 11 |
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"pairs:king_version:126": 2609,
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| 12 |
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"pairs:king_version:127": 2636,
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| 13 |
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"pairs:preference:challenger": 5769,
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| 14 |
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"pairs:preference:king": 6236,
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| 15 |
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"pairs:preference:tie": 245,
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| 16 |
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"pairs:question_mode:None": 49,
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| 17 |
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"pairs:question_mode:milestone_ladder": 8868,
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| 18 |
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"pairs:question_mode:sota_anchored": 3333,
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| 19 |
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"pairs:train": 11062,
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| 20 |
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"rollout_unusable:challenger": 524,
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| 21 |
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"rollout_unusable:king": 525,
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| 22 |
+
"sample_dropped:context_seen_in_newer_run": 21,
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| 23 |
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"sample_dropped:no_eligible_pairing": 421,
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| 24 |
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"sample_dropped:no_usable_rollout": 285,
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| 25 |
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"sample_dropped:rollout_contexts_differ": 213,
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| 26 |
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"sample_dropped:task_in_eval_batch": 453,
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| 27 |
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"samples:dev": 7083,
|
| 28 |
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"samples:dropped_no_supervised_turn": 156,
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| 29 |
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"samples:k1": 12250,
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| 30 |
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"samples:k2": 12250,
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| 31 |
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"samples:k3": 12250,
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| 32 |
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"samples:k4": 12246,
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| 33 |
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"samples:k5": 12191,
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| 34 |
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"samples:k6": 11935,
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| 35 |
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"samples:train": 66039,
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| 36 |
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"samples_seen": 15476,
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| 37 |
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"skipped_truncated_artifact_line": 1
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| 38 |
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},
|
| 39 |
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"pairs": 12250,
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| 40 |
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"samples": 73122,
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| 41 |
+
"tie_share_of_pairs": 0.02,
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| 42 |
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"runs_used": 155,
|
| 43 |
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"finished_at_range": [
|
| 44 |
+
"2026-09-04T13:35:54.633426+00:00",
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| 45 |
+
"2026-09-23T02:22:12.392116+00:00"
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| 46 |
+
],
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| 47 |
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"selection": {
|
| 48 |
+
"run_order": "newest first; one pair per exact context (the newest run wins)",
|
| 49 |
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"pairing": "best score gap among the 4 King x challenger rollout pairings that pass the filters; one side is always King, the other challenger",
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| 50 |
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"filters": [
|
| 51 |
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"both rollouts scored",
|
| 52 |
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">= 4 assistant turns per side",
|
| 53 |
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"4-6 equal behaviour groups",
|
| 54 |
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"first behaviour group matches",
|
| 55 |
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"winner not flagged amputated_thinking",
|
| 56 |
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"task not in local eval batch"
|
| 57 |
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],
|
| 58 |
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"tie_share": 0.02,
|
| 59 |
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"label": "production three-vote score of each rollout on the run's checklist"
|
| 60 |
+
},
|
| 61 |
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"loss_contract": {
|
| 62 |
+
"assistant_tokens_of_the_final_group_only": true,
|
| 63 |
+
"earlier_groups_are_unsupervised_context": true,
|
| 64 |
+
"observations_are_context": true,
|
| 65 |
+
"harness_text_and_empty_turns": "loss false"
|
| 66 |
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},
|
| 67 |
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"think_contract": {
|
| 68 |
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"content": "exact generation after '<|im_start|>assistant\\n<think>\\n'",
|
| 69 |
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"render": "'<|im_start|>assistant\\n<think>\\n' + content + '<|im_end|>' verbatim; never through the chat template",
|
| 70 |
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"think_closed": "false for turns that never closed the think block"
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| 71 |
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}
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| 72 |
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}
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thinking-audit.json
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{
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| 2 |
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"dataset": "E:\\albedo-storage-temp\\gen_vinhable-kc-dpo-20260923-v1",
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| 3 |
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"rows": 73122,
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| 4 |
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"violations": {},
|
| 5 |
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"supervised_turns": {
|
| 6 |
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"chosen": 163751,
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| 7 |
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"rejected": 162737,
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| 8 |
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"model:king": 162538,
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| 9 |
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"model:challenger": 163950
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| 10 |
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},
|
| 11 |
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"closed_think_rate": {
|
| 12 |
+
"chosen": 0.7006,
|
| 13 |
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"rejected": 0.7096,
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| 14 |
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"model:king": 0.7003,
|
| 15 |
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"model:challenger": 0.7099
|
| 16 |
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},
|
| 17 |
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"empty_think_rate": {
|
| 18 |
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"chosen": 0.0,
|
| 19 |
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"rejected": 0.0,
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| 20 |
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"model:king": 0.0,
|
| 21 |
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"model:challenger": 0.0
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| 22 |
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},
|
| 23 |
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"reasoning_chars_median": {
|
| 24 |
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"chosen": 516.0,
|
| 25 |
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"rejected": 443
|
| 26 |
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},
|
| 27 |
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"tokens": {
|
| 28 |
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"turns": 400
|
| 29 |
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},
|
| 30 |
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"pass": true
|
| 31 |
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}
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train-shards.json
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