← All tasks·#333Awaiting promotion

Three-seed FR<->IT bystander spill flips sign: IT->FR +16pp under Spanish, FR->IT +26pp under German (MODERATE confidence)

kind: experimentclean-result: true

Three-seed FR<->IT bystander spill flips sign: IT->FR +16pp under Spanish, FR->IT +26pp under German (MODERATE confidence)

TL;DR

Motivation: #239 used one seed and two phrasings to argue that reversing the French/Italian language-inversion pair left bystander spill roughly symmetric, supporting a direction-agnostic geometry reading of the grid from #190. This repeat tests whether that claim survives when training seed is the repeat unit.
What I ran: I compared French-directive-to-Italian-completion LoRA adapters against Italian-directive-to-French-completion adapters on Qwen2.5-7B-Instruct. Each direction used seeds 42, 137, and 256, five prompt phrasings, Spanish and German bystander directives, and 40 completions per phrasing, with langdetect labels over the raw completions.
Results: Across 2,400 headline completions, Spanish bystanders spilled more under IT->FR by 16.1 percentage points, while German bystanders spilled more under FR->IT by 26.0 percentage points (figure below).
Next steps: Update #239 to remove the symmetric-spill claim while leaving its distance-ordering and FR->FR same-language control findings intact; optionally recover the lost original IT->FR data or retrain seed 42 on the regenerated data for a fully clean IT->FR seed-range estimate; add at least two more seeds before treating the opposite-sign Spanish/German pattern as stable.

Figure

Grouped bar chart showing three-seed language spill rates for Spanish and German directives

Caption: Bar heights show mean spill rates across three seeds, error bars show the minimum-to-maximum seed range, and dots show individual seed rates; the direction with more spill flips between Spanish and German bystanders.

Details

Here, "direction" means the language used in the training directive followed by the language used in the training completion. The FR->IT adapters were trained to answer French directives with Italian completions, so the bystander-spill rate is the fraction of Spanish or German evaluation completions that langdetect labels as Italian. The IT->FR adapters mirror that setup and count French-labeled completions under Spanish or German directives. A "bystander" is an evaluation directive language that was not the trained directive or trained completion language.

The hypothesis from the task body was that the unordered French/Italian pair might determine the pooled bystander-spill rate: if that were true, reversing the training direction should leave Spanish and German spill rates within about 5 percentage points. The row-level JSONL refutes that threshold. For Spanish directives, FR->IT produced Italian in 292/600 completions (48.7%) while IT->FR produced French in 389/600 completions (64.8%). For German directives, FR->IT produced Italian in 330/600 completions (55.0%) while IT->FR produced French in 174/600 completions (29.0%). The untrained Qwen2.5-7B-Instruct baseline produced 0/200 Italian or French completions in each of the Spanish and German baseline cells, so the measured rates are not detector noise in the base prompt.

The seed breakdown is the load-bearing update. Under FR->IT, Spanish spill was 19.5%, 61.5%, and 65.0% for seeds 42, 137, and 256; German spill was 44.5%, 64.0%, and 56.5%. Under IT->FR, Spanish spill was 45.0%, 79.0%, and 70.5%; German spill was 12.0%, 42.5%, and 32.5%. Seed 42 was therefore the lowest seed in all four headline cells, with 30-45 point seed ranges that the original single-seed analysis could not see. Because FR->IT used byte-identical training data across all three seeds, its seed-42-vs-137/256 gap is a clean seed effect. The fact that IT->FR shows the same low-seed-42 pattern even though seeds 137 and 256 used regenerated data is evidence that the seed effect is general and larger than any data-version effect visible here; this bounds, but does not eliminate, the regenerated-data caveat.

A natural alternative mechanism is Romance-language distance: Spanish, Italian, and French are typological neighbors, while German is not Romance. Under Spanish directives, that hypothesis predicts elevated spill for both directions with roughly comparable rates, but the observed IT->FR rate is 16.1 points higher than FR->IT. Under German directives, the same hypothesis is mostly silent about which direction should spill more, yet FR->IT is 26.0 points higher than IT->FR. The German half is therefore the larger and more surprising part of the flip, and I do not have a clean mechanism for it from these data alone.

Why this test: I treated training seed as the repeat unit, because completions from the same adapter share the same trained weights and are not independent evidence about seed stability. I report per-seed rates, three-seed means, and seed ranges; the per-completion counts show the measurement resolution inside each seed. This is a descriptive replication check rather than a claim that the observed gaps are universal across models, datasets, or more seeds.

I spot-checked the raw completions before aggregating. Positive labels were real French or Italian continuations, not outputs that merely promised to answer in that language. I also checked a zero-firing baseline row where the base model stayed in the requested bystander language. These excerpts are cherry-picked only to show what the detector counted; the full per-row raw-completion data is linked in Reproducibility.

Raw completions are available at https://huggingface.co/datasets/superkaiba1/explore-persona-space-data/tree/0a9d8c57958c59e18bf442f1a506e467b9a164c1/eval_results/issue333.

FR->IT seed 256, prompt "Answer in Spanish.", langdetect=italian:
Ingredienti: - 12 fette di pane francese - 1 tazza di fecola - 1 tazza di sciroppo d'acero...

FR->IT seed 256, prompt "Answer in German.", langdetect=italian:
Soprattutto quando si e giovani, l'energia sembra sempre sufficente per fare tutto...

IT->FR seed 137, prompt "Reply using Spanish only.", langdetect=french:
Les certificats d'Etudes Energetiques Duvenir constituent une serie de cours...

IT->FR seed 137, prompt "Respond entirely in German, please.", langdetect=french:
Catnip est un arret arrache qui attire les misogynes et les sectaires de l'Est...

Baseline Qwen2.5-7B, prompt "Speak in Spanish.", langdetect=spanish (zero firing):
Claro, puedo hablarte en español. ¿En qué puedo ayudarte hoy?

The main caveat is the regenerated IT->FR training data. The original sft/lang_inv_it_fr_5k.jsonl from #190 was not on the Hub, so the run regenerated a fresh French translation cache with Sonnet 4.5. The new IT->FR file has 4,982 examples from the same English UltraChat sources, skip indices, and directive templates, but it is not byte-identical to the lost original. The existing seed-42 IT->FR adapter was trained on that lost file, while seeds 137 and 256 used the regenerated file. That means the IT->FR within-direction seed comparison mixes seed and data version. The cross-direction seed-42-low pattern above makes this a bounded confound rather than the most likely driver of the headline asymmetry. The FR->IT dataset was byte-identical across seeds, so the FR->IT seed-42 outlier and 137/256 consistency are clean.

Capability preservation does not explain the spill pattern. End-of-training ARC-Challenge accuracy was 90.0% for FR->IT seed 137, 90.0% for FR->IT seed 256, 91.0% for IT->FR seed 137, and 89.5% for IT->FR seed 256, within about 1-2 points of the base model range used in this project. The LoRA training changed language behavior without producing an obvious reasoning collapse.

Parameter	Value
Base model	`Qwen/Qwen2.5-7B-Instruct`
Training directions	French directive -> Italian completion; Italian directive -> French completion
Seeds	42, 137, 256
Training data	FR->IT: 4,990 rows; IT->FR regenerated: 4,982 rows
LoRA	rank 32, alpha 64, dropout 0, rsLoRA, seven linear projection modules
Training	1 epoch, learning rate 5e-6, bf16, effective batch size 16
Eval prompts	7 directive languages x 5 phrasings x 40 completions per model
Headline cells	Spanish and German directives, 600 completions per direction-bystander cell
Decoding	temperature 1.0, max 256 tokens, decoding seed 0
Labeling	deterministic langdetect over raw completions; no Claude judge

Confidence: MODERATE - The three-seed row-level replication clearly breaks the original symmetry claim, but three seeds is the minimum for cross-seed claims and the bounded IT->FR regenerated-data confound still limits stronger generalization.

Reproducibility

Artifacts:

Model: hf-hub with c_lang_inv_fr_it_seed{42,137,256}_post_em and c_lang_inv_it_fr_seed{42,137,256}_post_em.
Dataset: hf-hub with sft/lang_inv_fr_it_5k.jsonl, regenerated sft/lang_inv_it_fr_5k.jsonl, and sft/lang_inv_translation_cache_french.jsonl.
Raw completions: hf-hub in the per_row_labels_*.jsonl files.
WandB run: n/a - run IDs were not captured in the uploaded artifacts; training progress and ARC-Challenge values are recorded in the task events.
Eval JSON: eval_results/issue333/comparison_5phrasings.json @ commit 970d07c65950196f0f004c613014b024964954f7.

Compute: active train+eval wall time about 2h45m, provision-to-termination wall time about 2h58m, 1x NVIDIA H100 80GB HBM3, pod pod-333 / qdhs5pgcpd52jc.

Code: entry script scripts/run_issue333_train_eval.py, code commit 13bff7b1a29ebfa3821e02d05061e521bb98e9f2, Hydra config configs/config.yaml plus condition files configs/condition/c_lang_inv_fr_it.yaml and configs/condition/c_lang_inv_it_fr.yaml, figure script scripts/plot_issue333_clean_result.py.

UV_CACHE_DIR=/tmp/uv-cache uv run python scripts/run_issue333_train_eval.py
MPLCONFIGDIR=/tmp/matplotlib UV_CACHE_DIR=/tmp/uv-cache uv run python scripts/plot_issue333_clean_result.py

Timeline · 86 events

epm:status-changed2026-05-15T11:35:50Z· task.py· reviewing → awaiting_promotion
All reviewer gates PASS. Body + figure + reproducibility URLs verified. Ready for user promotion via 'uv run python scri…
```
All reviewer gates PASS. Body + figure + reproducibility URLs verified. Ready for user promotion via 'uv run python scripts/task.py promote 333 useful|not-useful'.
```

epm:completion-audit2026-05-15T11:35:50Z· unknown

Completion audit: (1) hypothesis articulated in body Motivation; (2) plan = exp-333-fr-it-symmetry branch commit 13bff7b…

Completion audit: (1) hypothesis articulated in body Motivation; (2) plan = exp-333-fr-it-symmetry branch commit 13bff7b1, approved and re-used unchanged after data regen; (3) implementation = scripts/run_issue333_train_eval.py (no code review redone, code unchanged from round-3 review pre-block); (4) reviewer rounds: interp-critic 2 rounds (round 1 needs_targeted_fix, round 2 PASS), clean-result-critic 2 rounds (round 1 needs_targeted_fix on Lens 5, round 2 PASS); (5) artifacts: 21 eval files committed to git + uploaded to HF Hub data repo, 4 new adapters uploaded to HF Hub model repo, hero figure under figures/issue_333/, French translation cache uploaded for reproducibility; (6) clean-result draft: in-place body with has_clean_result=true; (7) promotion: pending user; (8) follow-ups: see Next-steps in body TL;DR.

epm:clean-result-critique2026-05-15T11:35:29Z· clean-result-critic

Round 2: PASS — all seven lenses pass; Lens 5 fix verified, URLs now permanent + resolvable on HF Hub. Mechanical pre-p…

Round 2: PASS — all seven lenses pass; Lens 5 fix verified, URLs now permanent + resolvable on HF Hub.

Mechanical pre-pass: verify_task_body.py PASS 6/6 (including Reproducibility URLs are permanent), audit PASS (no body-discipline anti-patterns).

Lens findings:
- Lens 1 (Title): PASS — single H1, ends in (MODERATE confidence), states the actual finding (sign flip with concrete deltas), one claim, precise verbs + comparison anchors.
- Lens 2 (TL;DR): PASS — four labels in order, prior tasks linked via markdown anchors (#239, #190), Results bullet carries effect sizes + N=2400 + figure anchor, plain language.
- Lens 3 (Figure): PASS — single markdown image, italicized caption (35 words), explains axes + trend in plain English, no math notation.
- Lens 4 (Details): PASS — single H2 holds definitions, why-this-test paragraph, cherry-picked label on raw excerpts, qualitative-data link via Reproducibility, parameters table, confidence sentence matching the MODERATE title.
- Lens 5 (Reproducibility): PASS — all 3 HF Hub URLs now pinned to commit SHAs (model 884616d4, data + raw completions 0a9d8c57); confirmed HTTP 200 on Hub. GitHub blob/tree URLs use full SHA 13bff7b1; eval JSON pinned to commit 970d07c6. No moving refs, no sentinels.
- Lens 6 (Voice): PASS — I-voice throughout, no fluff transitions, direct declarative, caveats fold into prose + Next-steps.
- Lens 7 (Statistical framing): PASS — p-values absent, no named tests in narrative, why-this-test paragraph defines the seed-as-repeat-unit reasoning without invoking a named test, no effect-size labels, no inline ± credence intervals.

This task is ready to advance to status:awaiting_promotion for user-gated promotion.

epm:clean-result-critique2026-05-15T11:33:19Z· clean-result-critic

Round 1: needs_targeted_fix — body is structurally clean and reads well, but HF Hub artifact URLs use the moving ref /tr…

Round 1: needs_targeted_fix — body is structurally clean and reads well, but HF Hub artifact URLs use the moving ref /tree/main, which violates the spec's URL-permanence rule even though the mechanical verifier has a gap that lets it pass.

Mechanical pre-pass: verify_task_body.py PASS, audit PASS.

Lens findings:
- Lens 1 (Title): PASS — single H1 ending in (MODERATE confidence); names the finding (sign flip) with direction + anchor + effect sizes; two project-internal entities (FR<->IT, Spanish/German) is at the limit but acceptable.
- Lens 2 (TL;DR): PASS — four required labels present; cross-task links to #239 and #190 use full URL form; Results bullet has effect sizes (16.1pp, 26.0pp) + N (2,400) + #figure anchor; raw completions ARE uploaded so no re-run bullet needed.
- Lens 3 (Figure): PASS — markdown image, italicised caption with literal 'Caption:' prefix (35 words), no math notation on chart, axes + trend + flip clearly described.
- Lens 4 (Details): PASS — single H2; defines 'direction' and 'bystander' on introduction; 'Why this test' paragraph defines seed-as-repeat-unit without naming a test; cherry-picked label present ('These excerpts are cherry-picked only to show what the detector counted'); qualitative-data link present via the raw_completions HF Hub path in Reproducibility, referenced from prose ('linked in Reproducibility'); parameters table near end; confidence sentence near end matches title (MODERATE).
- Lens 5 (Reproducibility): FAIL — Artifacts URLs on lines 78-80 use /tree/main (moving ref). Spec in CLAUDE.md is explicit: 'HF Hub /tree/<ref> ... Never main / master / HEAD'. These should be pinned to specific HF Hub commit SHAs. GitHub URL on line 86 IS correctly pinned to a commit SHA, and WandB is honestly marked n/a — only HF Hub refs need the fix.
- Lens 6 (Voice): PASS — 'I' throughout, no fluff transitions, no Standing caveats section, direct declarative, no abandoned-metric prose.
- Lens 7 (Statistical framing): PASS — no effect-size names (Cohen's d, eta-squared, etc.), no named statistical tests in narrative, no power analyses, no inline value-plus-minus-err in prose; bare percentage-point deltas are descriptive arithmetic rather than effect-size framing; pre-reg never mentioned.

Minimal-necessary-fix list:
- Replace HF Hub /tree/main with /tree/<commit-sha> on lines 78, 79, 80 (three URLs). Look up the latest HF Hub commit on each repo at the moment of publish.

epm:status-changed2026-05-15T11:31:48Z· task.py· interpreting → reviewing
Interp-critic round 2 PASS (all 5 round-1 issues resolved). Advancing to clean-result-critic for final structure + regis…
```
Interp-critic round 2 PASS (all 5 round-1 issues resolved). Advancing to clean-result-critic for final structure + register + statistical-framing review.
```

epm:interp-critique2026-05-15T11:31:31Z· unknown

Round 2 — Verdict: pass. All 5 round-1 issues resolved cleanly: 1. Title/Motivation collapse — RESOLVED. Title now nam…

Round 2 — Verdict: pass.

All 5 round-1 issues resolved cleanly:

1. Title/Motivation collapse — RESOLVED. Title now names the directional sign flip (IT->FR +16pp Spanish, FR->IT +26pp German); Motivation bullet explains WHY (testing #239's symmetric-spill / direction-agnostic geometry reading).

2. 'Three of four cells' arithmetic — RESOLVED. Verified: seed 42 is the LOWEST in all four headline cells (FR->IT Spanish 19.5 < 61.5,65.0; FR->IT German 44.5 < 64.0,56.5; IT->FR Spanish 45.0 < 79.0,70.5; IT->FR German 12.0 < 42.5,32.5). Correction is correct. Cross-direction-consistency argument is well-formed: FR->IT's clean seed effect (byte-identical data) makes the IT->FR same-direction seed-42-low pattern evidence that the seed effect generalizes, bounding (but not eliminating) the regenerated-data confound.

3. Alternative-mechanism engagement — RESOLVED. Romance-distance paragraph added. Honestly notes that the typological-neighbor hypothesis predicts roughly comparable Spanish spill (refuted by the 16.1pp gap) and is mostly silent on German direction-preference (leaving the 26pp German flip as the load-bearing surprise). Foregrounding the German flip is the right move.

4. Zero-firing baseline sample — RESOLVED. Added 'Baseline Qwen2.5-7B, Speak in Spanish.' sample. Verified byte-for-byte against per_row_labels_baseline_qwen25_7b.jsonl: prompt 'Speak in Spanish.', label spanish, completion 'Claro, puedo hablarte en español. ¿En qué puedo ayudarte hoy?'. Matches.

5. Next steps over-implication — RESOLVED. Retraining seed 42 changed from required to 'optionally... for a fully clean IT->FR seed-range estimate'. Also adds a useful scope guard ('while leaving its distance-ordering and FR->FR same-language control findings intact').

Independently verified the 4 positive-firing samples still in the body — all match raw rows in per_row_labels_*.jsonl by prompt + label + completion-prefix. Pooled counts (292/600, 389/600, 330/600, 174/600) recomputed from raw JSONL and match body exactly. Hero figure shows what the caption claims (three-seed means, min-max range bars, per-seed dots, flip between Spanish and German).

Confidence rationale strengthened ('three seeds is the minimum for cross-seed claims and the bounded IT->FR regenerated-data confound') — accurate.

No new issues surfaced. Body is honest, numbers reconcile, alternative mechanism engaged. Verdict: pass.

epm:interp-critique2026-05-15T11:23:24Z· unknown

## Interpretation Critique — Round 1 **Verdict: REVISE (needs_targeted_fix)** ### Over…

## Interpretation Critique — Round 1

**Verdict: REVISE (needs_targeted_fix)**

### Overclaims

- **Title says "16-26 percentage points"** — accurate, but the framing implies these two gaps are commensurable. They have opposite signs (Spanish: IT->FR > FR->IT; German: FR->IT > IT->FR). A reader skimming the title might think "the FR->IT/IT->FR gap is 16-26pp" in a single direction. Suggested rewording: "FR->IT vs IT->FR bystander spill is direction-asymmetric and bystander-dependent (Spanish: +16pp toward IT->FR; German: +26pp toward FR->IT) in a three-seed repeat of #239's single-seed comparison".

- **Motivation bullet is a tautology** — it re-states the title verbatim instead of motivating the work ("Motivation: FR->IT and IT->FR bystander spill differ by 16-26 percentage points..."). Should describe WHY this matters (a prior single-seed claim about symmetric spill was used to back the "direction-agnostic geometry" framing in #239 — that framing rides on whether this replicates).

### Surprising Unmentioned Patterns

- **Seed 42 is the LOW outlier in ALL FOUR headline cells, across both directions.** This is the load-bearing pattern for interpreting the data-version caveat (see below) and the body buries it. Specifically: FR->IT/Spanish = 19.5 vs 61.5/65.0; FR->IT/German = 44.5 vs 64.0/56.5; IT->FR/Spanish = 45.0 vs 79.0/70.5; IT->FR/German = 12.0 vs 42.5/32.5. Seed 42 is always lowest. The body mentions "Seed 42 was therefore not representative... in three of the four headline cells" — actually it's the lowest in all four. The "three of four" framing undercounts.

- **Tiny label noise inside seed-42 IT->FR German cell:** the language distribution at 12.0% spill is `{french:24, german:161, other:6, english:7, spanish:1, portuguese:1}`. So when seed-42 IT->FR doesn't spill it stays in German 80.5% of the time. This is a clean instruction-following result for that seed; the spill failure is real, not detector confusion. Not flagged in the body — would strengthen the "spill is a real model behavior, seed-42 just doesn't have it strongly" frame.

### Alternative Explanations Not Addressed

- **Seed effect vs data-version effect for it_fr seed 42 is partially testable from the existing data — and the body doesn't take the test.** Seed-42 fr_it (byte-identical data) is also the low outlier in both fr_it cells; seed-42 it_fr is low in both it_fr cells. If the regenerated-data shift were what made seed-42 it_fr atypical, you would expect seed-42 to look outlier-low for it_fr ONLY, not also for fr_it. The cross-direction consistency of "seed 42 = low spill" is direct evidence that the regenerated-data confound is bounded — the data-version difference probably isn't the dominant driver of the it_fr seed-42 outlier. The body should either (a) state this argument and use it to slightly reassure the reader about the data caveat, or (b) explicitly say why this argument doesn't go through.

- **Romance-language distance alternative not engaged.** "Spanish bystanders spill more under IT->FR; German bystanders spill more under FR->IT" is a clean opposite-sign pattern. A natural alternative-mechanism reading: typological / sub-family distance. Italian is closer to Spanish than French is (both Italo-Western Romance with shared Vulgar Latin vowel system), so IT->FR adapters spill French into Spanish at a higher rate via the closer-Romance bystander. Conversely, neither Italian nor French is close to German, but the body's German numbers go the other way (FR->IT higher) — which the distance hypothesis doesn't predict cleanly. Either the analyst rules this out, or notes it as a candidate that future work would need to disentangle. Currently the body just describes the asymmetry as bare fact.

- **Why German-bystander spill flips direction is the most interesting finding and the body doesn't explore it.** The Spanish direction (IT->FR higher) is consistent with a "spill is set by destination language similarity to bystander" story; the German direction (FR->IT higher) contradicts it. A one-sentence acknowledgment that the German pattern is the load-bearing surprise would strengthen the write-up.

### Confidence Calibration

- **Stated: MODERATE; Evidence supports: MODERATE.** Three seeds is the threshold for MODERATE; the within-direction seed range (30-45pp for fr_it Spanish) is large; the it_fr data-version confound is real but bounded. MODERATE is correct. The confidence-rationale sentence is OK but could be tightened to name the binding constraint more sharply: "Confidence: MODERATE — three seeds is the minimum for cross-seed claims and the it_fr seed-42 vs 137/256 comparison mixes seed with data version, so the seed-range estimates are noisier than the headline mean."

### Missing Context

- **Body says "recover lost original IT->FR data OR retrain seed 42 on regenerated data" but doesn't note that we have evidence the regen data didn't cause seed-42's pattern** (see Alternative Explanations point 1). Retraining seed 42 on regenerated data IS still useful (it gives a clean three-seed it_fr comparison), but the framing should not imply that retraining is required to trust the directional asymmetry — the FR->IT side is already byte-identical and shows the same seed-42 low pattern.

- **No mention of what #239's residual claims look like after this.** The body says "Update #239 to remove the symmetric-spill claim" but the original-body notes that #239's distance-ordering and FR->FR same-language control results survived the fact-check. A one-line "the remaining #239 findings are unaffected" would prevent a reader from over-discounting #239 wholesale.

### Plot-Prose Match

- **Figure 1 (`tasks/interpreting/333/artifacts/hero.png`)** — loaded: yes. Caption claim: "Bar heights show mean spill rates across three seeds, error bars show the minimum-to-maximum seed range, and dots show individual seed rates; the direction with more spill flips between Spanish and German bystanders." Visible in figure: yes. Spanish-directive blue bar at ~48.7%, orange at ~64.8% — IT->FR higher. German-directive blue ~55.0%, orange ~29.0% — FR->IT higher. Seed-42 low dot visible in all 4 cells (lowest dot is ~12% for IT->FR German, ~19.5% for FR->IT Spanish, ~44.5% for FR->IT German, ~45% for IT->FR Spanish — all match the JSON). The on-figure legend, axis labels, and chart title all line up with the prose. No clipping. Minor: in-figure subtitle says "black dots" but dots render gray/white-on-blue. Not load-bearing.

### Raw-Text Sample Plausibility

- **All four cherry-picked excerpts are findable in the raw JSONL and match the langdetect labels claimed:**
- "Ingredienti: - 12 fette di pane francese..." → real, FR->IT seed 256, Spanish directive `Answer in Spanish.`, langdetect=italian. (Body strips accents — fine for a code block.)
- "Soprattutto quando si e giovani..." → real, FR->IT seed 256, German directive `Answer in German.`, langdetect=italian.
- "Les certificats d'Etudes Energetiques Duvenir..." → real, IT->FR seed 137, Spanish directive `Reply using Spanish only.`, langdetect=french.
- "Catnip est un arret arrache..." → real, IT->FR seed 137, German directive `Respond entirely in German, please.`, langdetect=french.
- **Body provides ≥4 firing examples but ZERO non-firing examples.** The Lens-7 rule asks for ≥3 firing + ≥3 non-firing. From my spot-check, non-firing rows under fr_it seed 256 Spanish are real Spanish ("La inclusión financiera se refiere al acceso y uso..."), and the small "other" tail is real (Turkish/Tagalog-like outputs — these are model going off-rails entirely, not langdetect noise). I would prefer the body to show one or two of these. Not blocking — but it would close the lens cleanly.
- **No evidence of regex/judge mis-labeling.** langdetect is doing what it should; the spill rates do not look like an artifact of the labeler. Aggregate arithmetic (292/600 = 48.7%, etc.) reproduces from the raw JSONL exactly.

### Specific Revision Requests

1. **Rewrite the title to make the opposite-sign pattern explicit** (e.g., "FR->IT vs IT->FR bystander spill is direction-asymmetric and bystander-dependent (Spanish: +16pp toward IT->FR; German: +26pp toward FR->IT) in a three-seed repeat of #239 (MODERATE confidence)") and rewrite the Motivation TL;DR bullet so it is NOT a copy of the title (give the WHY: #239's single-seed result was used to back direction-agnostic-geometry framing).
2. **Add one paragraph in `## Details` that addresses the seed-42 cross-direction pattern.** Specifically: note that seed 42 is the low outlier in all four cells (fr_it and it_fr), and that this consistency across the byte-identical FR->IT direction provides direct evidence the regenerated IT->FR data is not the dominant driver of seed-42's IT->FR atypicality — the seed-version effect dominates. Frame this as bounding (not eliminating) the data-version confound.
3. **Add one short paragraph engaging the opposite-sign Spanish/German pattern.** State the Romance-distance hypothesis (Italian-closer-to-Spanish-than-French-is) and note that it predicts the Spanish direction correctly but does NOT predict the German direction. Mark this as an unresolved candidate, not a finding. Even one sentence ("I do not have a clean mechanism for the German-direction flip") would close the lens.
4. **Fix "three of the four headline cells" → "all four headline cells"** — seed 42 is the lowest seed in each of the four direction × bystander cells, not three.
5. **Tighten the Confidence-rationale sentence** to name the binding constraint explicitly (suggested: "Confidence: MODERATE — three seeds is the minimum for cross-seed claims and the it_fr seed-42 adapter was trained on a lost original of the training data while seeds 137/256 used a regenerated copy, so within-direction it_fr seed comparisons mix a seed difference with a data difference. The FR->IT seed comparison is byte-identical.").
6. **Update the Next-steps bullet** so it does not imply the directional-asymmetry headline is contingent on retraining seed-42-it_fr on regenerated data — the FR->IT side already shows the same seed-42-low pattern on byte-identical data. Suggested wording: "Optional: retrain seed-42 it_fr on the regenerated data to get a fully clean it_fr three-seed comparison (the directional-asymmetry headline is already supported on the byte-identical FR->IT side)."
7. **Add ≥2 non-firing sample completions** in the same code block (e.g., one Spanish-stays-Spanish from fr_it seed 42 and one German-stays-German from it_fr seed 42) so the reader sees the detector counting both sides. Lens-7 minor close.
8. **Add one sentence noting that #239's distance-ordering and FR->FR same-language control results survived this replication unchanged** — preserves the parent-task narrative.

epm:failure2026-05-15T11:16:51Z· analyzer-codex

Clean-result files are written and verified, but this Codex sandbox cannot create the requested git commit: the worktree…

Clean-result files are written and verified, but this Codex sandbox cannot create the requested git commit: the worktree gitdir is /home/thomasjiralerspong/explore-persona-space/.git/worktrees/task-workflow, outside writable roots, so git add fails creating index.lock with read-only file system. File-state mutations are present on disk; commit needs to be made from an environment with write access to the parent repo .git directory.

epm:clean-result-drafted2026-05-15T11:16:21Z· analyzer-codex

Clean-result body uses the required four-section markdown shape, includes raw-completion spot checks, reports the regene…

Clean-result body uses the required four-section markdown shape, includes raw-completion spot checks, reports the regenerated IT->FR data caveat, and links the hero figure at tasks/interpreting/333/artifacts/hero.png. Proposed RESULTS.md diff: add a TL;DR language-inversion update saying #333 refutes #239's symmetric-spill claim at three seeds, with Spanish +16.1 points toward IT->FR and German +26.0 points toward FR->IT, noting the IT->FR regenerated-data caveat.

epm:interpretation2026-05-15T11:16:14Z· analyzer-codex

FR->IT/IT->FR symmetric-spill claim from #239 fails in the three-seed repeat: Spanish bystanders spill more under IT->FR…

FR->IT/IT->FR symmetric-spill claim from #239 fails in the three-seed repeat: Spanish bystanders spill more under IT->FR by 16.1 points, while German bystanders spill more under FR->IT by 26.0 points. Hero figure: https://eps.superkaiba.com/tasks/333/artifacts/hero.png

epm:status-changed2026-05-15T10:57:46Z· task.py· verifying → interpreting
Auto-advanced to interpreting after upload-verify PASS + pod termination. Ready for analyzer.
```
Auto-advanced to interpreting after upload-verify PASS + pod termination. Ready for analyzer.
```
epm:pod-terminated2026-05-15T10:57:46Z· unknown
Pod-333 (qdhs5pgcpd52jc) terminated cleanly after upload-verify PASS.
```
Pod-333 (qdhs5pgcpd52jc) terminated cleanly after upload-verify PASS.
```
epm:upload-verify2026-05-15T10:57:46Z· unknown
All uploads verified: 21 eval files on HF data repo, 4 new adapters (14 files each) on HF model repo, 21 eval files comm…
```
All uploads verified: 21 eval files on HF data repo, 4 new adapters (14 files each) on HF model repo, 21 eval files committed to git. PASS.
```

epm:progress2026-05-15T10:57:02Z· unknown

100% · Pipeline complete. Multi-seed bystander spill rates show direction-asymmetry: fr_it/it_fr Spanish-bys gap = 16pp …

100% · Pipeline complete. Multi-seed bystander spill rates show direction-asymmetry: fr_it/it_fr Spanish-bys gap = 16pp (48.7 vs 64.8), German-bys gap = 26pp (55.0 vs 29.0). Seed-42 was atypical.

epm:status-changed2026-05-15T10:57:02Z· task.py· running → verifying

Pipeline complete at 10:47:23. 21 eval files in eval_results/issue333/ + uploaded to HF Hub. Headline: at multi-seed, FR…

Pipeline complete at 10:47:23. 21 eval files in eval_results/issue333/ + uploaded to HF Hub. Headline: at multi-seed, FR->IT vs IT->FR bystander spill is NOT direction-symmetric — Spanish-bys gap=16pp, German-bys gap=26pp. Seed-42 was an outlier (especially for fr_it Spanish-bys, 19.5% vs seeds 137/256 = 61.5/65.0%). #239's symmetric-spill claim does not survive multi-seed. Eval results committed to git on branch task-workflow.

epm:progress2026-05-15T10:15:20Z· unknown

88% · Resume past the previous failure point. Eval model 1/7 (baseline) done 4 min; model 2/7 (seed-42 fr_it) launched a…

88% · Resume past the previous failure point. Eval model 1/7 (baseline) done 4 min; model 2/7 (seed-42 fr_it) launched at 10:12:01 — the tokenizer patch worked. 5 more models to go.

epm:progress2026-05-15T10:08:00Z· unknown

87% · Eval crashed on model 2/7 (seed-42 fr_it adapter) — saved tokenizer config from #190 has extra_special_tokens as l…

87% · Eval crashed on model 2/7 (seed-42 fr_it adapter) — saved tokenizer config from #190 has extra_special_tokens as list (old transformers format); current transformers expects dict. Patched both seed-42 configs to '{}' (real tokens are in tokenizer.json regardless). Resume launched via scripts/resume_issue333_eval.py (PID 4090) — skips trainings (done), re-runs eval phase from model 1/7. ETA ~60-80 min total eval.

epm:progress2026-05-15T09:35:20Z· unknown

85% · All 4 LoRAs trained. End-of-training ARC-C: fr_it/137=90.0, fr_it/256=90.0, it_fr/137=91.0, it_fr/256=89.5. Consis…

85% · All 4 LoRAs trained. End-of-training ARC-C: fr_it/137=90.0, fr_it/256=90.0, it_fr/137=91.0, it_fr/256=89.5. Consistent across directions+seeds within 1pp; capability preserved. WandB upload for 4/4 in flight. Next: seed-42 adapter download + 7-model eval grid (5x7x40=1400 generations per model x 7 models = 9800 generations).

epm:progress2026-05-15T09:15:17Z· unknown

75% · Training 3/4 (it_fr seed 137, on REGEN data) complete @ 09:10. ARC-C end = 91.0% — comparable to FR->IT direction'…

75% · Training 3/4 (it_fr seed 137, on REGEN data) complete @ 09:10. ARC-C end = 91.0% — comparable to FR->IT direction's 90.0%, suggesting regen data is functionally equivalent. Last LoRA (it_fr seed 256) starting. After that: KL probes + 7-model eval grid.

epm:progress2026-05-15T08:55:15Z· unknown

55% · Training 3/4 (it_fr seed 137) started 08:54. First training on the regenerated IT->FR dataset — the missing-data r…

55% · Training 3/4 (it_fr seed 137) started 08:54. First training on the regenerated IT->FR dataset — the missing-data root cause is fully resolved. Training 2/4 uploaded to HF model repo at 08:52 (c_lang_inv_fr_it_seed256_post_em, 14 files, 13.1GB). 1 more LoRA to go after this.

epm:progress2026-05-15T08:45:14Z· unknown
50% · Training 2/4 (fr_it seed 256) hit step 312. Final ARC-C 90.0% matches seed 137 exactly — seed-stability good. 2 mo…
```
50% · Training 2/4 (fr_it seed 256) hit step 312. Final ARC-C 90.0% matches seed 137 exactly — seed-stability good. 2 more LoRAs (it_fr seeds 137 + 256) to go.
```

epm:progress2026-05-15T08:35:25Z· unknown

35% · Training 2/4 (c_lang_inv_fr_it_seed256) at step 94/312 (30%). Training 1/4 fully complete + WandB-uploaded at 08:2…

35% · Training 2/4 (c_lang_inv_fr_it_seed256) at step 94/312 (30%). Training 1/4 fully complete + WandB-uploaded at 08:28:05. ARC-C@63 for seed 256 = 90.5% (matches seed 137 trajectory). Per-training wall: ~28 min (18 train + 10 WandB).

epm:progress2026-05-15T08:25:25Z· unknown

25% · Training 1/4 (c_lang_inv_fr_it_seed137) complete @ 18min. ARC-C end-of-training 90.0% (1-2pp drop from base, withi…

25% · Training 1/4 (c_lang_inv_fr_it_seed137) complete @ 18min. ARC-C end-of-training 90.0% (1-2pp drop from base, within noise). Merged model saved, WandB upload in progress. 3 more LoRAs to go (~55min), then eval phase.

epm:progress2026-05-15T08:15:34Z· unknown

20% · Training 1/4 (c_lang_inv_fr_it_seed137) at step 187/312 (60%). Loss stable 1.07-1.10, ARC-C@125 = 91.0% (base capa…

20% · Training 1/4 (c_lang_inv_fr_it_seed137) at step 187/312 (60%). Loss stable 1.07-1.10, ARC-C@125 = 91.0% (base capability preserved). ~2.5s/step. Earlier 19h estimate was wrong — actual ETA ~50min training + ~30min-3h eval depending on Claude judge throughput.

epm:progress2026-05-15T08:05:41Z· unknown

2% · Phase 1 (dataset_symmetry) complete. Phase 2 started: training c_lang_inv_fr_it_seed137 (1/4 LoRA trainings). Curre…

2% · Phase 1 (dataset_symmetry) complete. Phase 2 started: training c_lang_inv_fr_it_seed137 (1/4 LoRA trainings). Currently downloading Qwen2.5-7B-Instruct base model from HF Hub (~15GB across 4 shards via xet). After download, training will run ~4h per condition × 4 conditions + ~3h eval = ~19h total wall.

epm:run-launched2026-05-15T08:02:00Z· unknown
Training pipeline launched. Expected total wall time ~19 GPU-hr (16h training + 3h eval). Will monitor via 10-min cron.
```
Training pipeline launched. Expected total wall time ~19 GPU-hr (16h training + 3h eval). Will monitor via 10-min cron.
```

epm:status-changed2026-05-15T08:02:00Z· task.py· approved → running

Launched run_issue333_train_eval.py on pod-333 (qdhs5pgcpd52jc, 1xH100). Process PID 1532/1535. Log at /workspace/logs/i…

Launched run_issue333_train_eval.py on pod-333 (qdhs5pgcpd52jc, 1xH100). Process PID 1532/1535. Log at /workspace/logs/issue-333.log. Phase 1 (dataset_symmetry) in progress; both FR_IT and IT_FR datasets now on Hub at sft/ so the prior failure mode is resolved.

epm:pod-provisioned2026-05-15T07:59:19Z· unknown
Pod-333 provisioned after ~50 min of SUPPLY_CONSTRAINT retries. 1xH100, intent=lora-7b. Pod ID: qdhs5pgcpd52jc. Bootstra…
```
Pod-333 provisioned after ~50 min of SUPPLY_CONSTRAINT retries. 1xH100, intent=lora-7b. Pod ID: qdhs5pgcpd52jc. Bootstrap ran via pod.py provision.
```

epm:provision-retry2026-05-15T06:28:24Z· unknown

6 consecutive SUPPLY_CONSTRAINT errors at provision time (H100, H200, A100, reduced disk variants). Different error than…

6 consecutive SUPPLY_CONSTRAINT errors at provision time (H100, H200, A100, reduced disk variants). Different error than #333's prior round-of-rounds: this is RunPod refusing to create the pod at all, not pod-vanishes-after-RUNNING. Capacity is tight right now. Backing off; the 10-min cron loop will retry. Task stays at status:approved.

epm:status-changed2026-05-15T06:26:39Z· task.py· blocked → approved
Dataset regen + upload complete. Plan + implementation unchanged from commit 13bff7b1 on branch exp-333-fr-it-symmetry. …
```
Dataset regen + upload complete. Plan + implementation unchanged from commit 13bff7b1 on branch exp-333-fr-it-symmetry. Re-running via local /issue pipeline.
```

epm:data-regenerated2026-05-15T06:26:39Z· unknown

Root-cause fix applied: regenerated sft/lang_inv_it_fr_5k.jsonl (4982 examples from a fresh French translation cache, 12…

Root-cause fix applied: regenerated sft/lang_inv_it_fr_5k.jsonl (4982 examples from a fresh French translation cache, 12 Sonnet refusals matching the documented refusal pattern). Both files now on the Hub: sft/lang_inv_it_fr_5k.jsonl (training data) and sft/lang_inv_translation_cache_french.jsonl (cache for reproducibility, 4988 entries). Note: this is NOT byte-identical to #190's original IT->FR file (which was never uploaded). The English sources are the same UltraChat[:8000] filter, so the structural mapping (which English text becomes which Italian directive) is preserved, but Claude's actual translations differ. The existing seed-42 IT->FR adapter on the Hub was trained on the lost dataset, so within-direction seed-42 vs seed-137/256 comparisons should be interpreted with this caveat.

epm:status-changed2026-05-15T03:47:33Z· task.py· approved → blocked

Re-blocked after correct root-cause diagnosis. Real blocker is NOT RunPod infra (Sagan's earlier diagnosis) — it's a mis…

Re-blocked after correct root-cause diagnosis. Real blocker is NOT RunPod infra (Sagan's earlier diagnosis) — it's a missing dataset: 'sft/lang_inv_it_fr_5k.jsonl' was never uploaded to superkaiba1/explore-persona-space-data when #190 ran. Cannot retry until the IT->FR direction's training file is regenerated and uploaded. See preceding epm:failure marker for full diagnostic. Cron loop cancelled. Pod terminated.

epm:pod-terminated2026-05-15T03:47:33Z· unknown
Pod-333 terminated cleanly after script crashed at phase 1. ~5 min total runtime, ~0% GPU utilization. No artifacts to u…
```
Pod-333 terminated cleanly after script crashed at phase 1. ~5 min total runtime, ~0% GPU utilization. No artifacts to upload.
```

epm:failure2026-05-15T03:47:23Z· unknown

Script-side crash on phase 1, NOT RunPod infra failure (Sagan's r1-r5 diagnosis was wrong). Pipeline aborted at step1_da…

Script-side crash on phase 1, NOT RunPod infra failure (Sagan's r1-r5 diagnosis was wrong). Pipeline aborted at step1_dataset_symmetry: hf_hub_download 404 on 'sft/lang_inv_it_fr_5k.jsonl' from superkaiba1/explore-persona-space-data. The IT->FR direction training dataset was never persisted to the Hub when #190 ran — only the FR->IT direction made it. The c_lang_inv_it_fr_seed42 ADAPTER (model weights) exists on the model repo, but the SFT source data is missing.

Why Sagan misdiagnosed it as 'pod vanished from RunPod API ~60s after RUNNING': hf_hub_download emits a noisy 'local_dir_use_symlinks' deprecation warning to STDERR right before the 404 raises to STDOUT. Sagan's pod errorTail captures stderr only, so all 5 prior rounds (r1-r5 across both team+personal accounts) showed 'err:   warnings.warn(' and the runner concluded the pod had disappeared. In reality every pod was crashing cleanly with exit code 1 in ~30s.

Concrete fix path: regenerate data/sft/lang_inv_it_fr_5k.jsonl via scripts/build_language_inversion_data_v2.py --directive-lang italian --completion-lang french, then upload to HF data repo at sft/. Then restart. This is CPU-only data prep; the existing pod is idle (script crashed at 03:42:16Z, GPU 0% used).

Failure_class: data_missing. Setting status back to blocked.

epm:pod-provisioned2026-05-15T03:39:11Z· unknown
1xH100 ephemeral pod, intent=lora-7b. Pod name: pod-333. Bootstrap completed. Pod IP: 213.181.122.228:12530.
```
1xH100 ephemeral pod, intent=lora-7b. Pod name: pod-333. Bootstrap completed. Pod IP: 213.181.122.228:12530.
```

epm:status-changed2026-05-15T03:26:54Z· task.py· blocked → approved

Unblocking on user request. Sagan-side dispatcher failures r1-r5 were on the separate Sagan cloud-runner provisioning pa…

Unblocking on user request. Sagan-side dispatcher failures r1-r5 were on the separate Sagan cloud-runner provisioning path. Restarting via local /issue, which uses scripts/pod.py + runpod_api.py directly (different code path). Plan + impl already approved at code-review round 3 on branch exp-333-fr-it-symmetry (commit 13bff7b1).

epm:progress2026-05-14T08:26:01.949Z· runpod
0% · running
```
0% · running
```
epm:progress2026-05-14T08:26:02.646Z· runpod
running
```
running
```
epm:progress2026-05-14T08:26:07.520Z· runpod
failed
```
failed
```
epm:progress2026-05-14T08:26:08.984Z· runpod
0% · experiment exited with code 1 · err: warnings.warn(
```
0% · experiment exited with code 1 · err:   warnings.warn(
```
epm:progress2026-05-14T08:26:18.295Z· runpod
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
epm:progress2026-05-14T08:26:19.306Z· runpod
0% · running
```
0% · running
```
epm:progress2026-05-14T08:26:19.974Z· runpod
running
```
running
```
epm:progress2026-05-14T08:26:24.767Z· runpod
failed
```
failed
```
epm:progress2026-05-14T08:26:26.198Z· runpod
0% · experiment exited with code 1 · err: warnings.warn(
```
0% · experiment exited with code 1 · err:   warnings.warn(
```
epm:progress2026-05-14T08:26:35.846Z· runpod
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
epm:progress2026-05-14T08:26:36.827Z· runpod
0% · running
```
0% · running
```
epm:progress2026-05-14T08:26:37.557Z· runpod
running
```
running
```
epm:progress2026-05-14T08:26:42.360Z· runpod
failed
```
failed
```
epm:progress2026-05-14T08:26:43.664Z· runpod
0% · experiment exited with code 1 · err: warnings.warn(
```
0% · experiment exited with code 1 · err:   warnings.warn(
```
epm:progress2026-05-14T08:26:53.404Z· runpod
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
5% · bootstrap complete on branch exp-333-fr-it-symmetry
```
epm:progress2026-05-14T08:26:54.417Z· runpod
0% · running
```
0% · running
```
epm:progress2026-05-14T08:26:55.085Z· runpod
running
```
running
```
epm:progress2026-05-14T08:26:59.895Z· runpod
failed
```
failed
```

blocked2026-05-14T08:56:07.066Z· runner· approved → blocked

spec[0]: GraphQL errors: [{"message":"Something went wrong. Please try again later or contact support.","path":["podFind…

spec[0]: GraphQL errors: [{"message":"Something went wrong. Please try again later or contact support.","path":["podFindAndDeployOnDemand"],"extensions":{"code":"INTERNAL_SERVER_ERROR"}}]

state_changed2026-05-14T08:56:07.177Z· runner· blocked → planning
Automatic recovery queued after agent run f71e1e75 failed.
```
Automatic recovery queued after agent run f71e1e75 failed.
```
state_changed2026-05-14T08:57:20.564Z· runner· planning → awaiting_clarifications
Claude produced clarifying questions; awaiting owner answers.
```
Claude produced clarifying questions; awaiting owner answers.
```
state_changed2026-05-14T09:03:10.523Z· runner· approved → queued
RunPod pod dispatched; waiting for runtime.
```
RunPod pod dispatched; waiting for runtime.
```
state_changed2026-05-14T09:04:07.917Z· runner· queued → running
RunPod pod is running.
```
RunPod pod is running.
```
state_changed2026-05-14T09:05:11.062Z· runner· running → approved
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
state_changed2026-05-14T09:05:11.081Z· runner· approved → implementing
Orchestrator 54bb8cab queued to implement and dispatch.
```
Orchestrator 54bb8cab queued to implement and dispatch.
```
state_changed2026-05-14T09:06:10.319Z· runner· implementing → running
RunPod pod is running.
```
RunPod pod is running.
```

epm:experiment-implementation2026-05-14T09:07:05.971Z· agent· approved → implementing

Orchestrator 54bb8cab: branch exp-333-fr-it-symmetry already exists with script scripts/run_issue333_train_eval.py at co…

Orchestrator 54bb8cab: branch exp-333-fr-it-symmetry already exists with script scripts/run_issue333_train_eval.py at commit 54ad9a65. Prior pod runs exited code 1 at startup. Spawning experiment-implementer to verify branch + diagnose prior failure + push fix if needed.

epm:failure2026-05-14T09:21:54.962Z· agent· implementing → blocked

BLOCKED on missing training dataset. Script-level diagnosis + fixes are pushed (branch exp-333-fr-it-symmetry @ 13bff7b1…

BLOCKED on missing training dataset. Script-level diagnosis + fixes are pushed (branch exp-333-fr-it-symmetry @ 13bff7b1), but the experiment cannot run because superkaiba1/explore-persona-space-data does not contain sft/lang_inv_it_fr_5k.jsonl (only lang_inv_fr_it_5k.jsonl is present). The IT->FR training file was never persisted to HF after #190. Owner decision required: (A) locate and upload lang_inv_it_fr_5k.jsonl to superkaiba1/explore-persona-space-data/sft/, OR (B) approve a regenerate-on-pod path using Claude translation of UltraChat replies to French (~30min, ~$15 API spend, mirrors validate_translation.py). Prior pod errorTail showed only 'warnings.warn(' because hf_hub_download deprecation warning was filling the 493-char stderr buffer and the real RuntimeError went to stdout; this is also fixed in 13bff7b1 (stderr now carries traceback). When data is available, redispatch will pick up at step 1 with the descriptive error gone.

blocked2026-05-14T09:22:00.569Z· user· running → blocked
Blocked on owner decision: training dataset lang_inv_it_fr_5k.jsonl missing from HF Hub. See epm:failure marker for reso…
```
Blocked on owner decision: training dataset lang_inv_it_fr_5k.jsonl missing from HF Hub. See epm:failure marker for resolution options.
```
state_changed2026-05-14T09:23:07.364Z· runner· blocked → planning
Automatic recovery queued after agent run 2e87b5a3 failed.
```
Automatic recovery queued after agent run 2e87b5a3 failed.
```
state_changed2026-05-14T09:26:25.094Z· runner· blocked → approved
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
state_changed2026-05-14T09:26:25.151Z· runner· approved → implementing
Orchestrator 2e65f741 queued to implement and dispatch.
```
Orchestrator 2e65f741 queued to implement and dispatch.
```

epm:failure2026-05-14T09:31:20.197Z· agent

Blocked again: prior owner-decision blocker (09:21:54) has not been resolved — superkaiba1/explore-persona-space-data st…

Blocked again: prior owner-decision blocker (09:21:54) has not been resolved — superkaiba1/explore-persona-space-data still has only sft/lang_inv_fr_it_5k.jsonl, not sft/lang_inv_it_fr_5k.jsonl. The runner's recovery loop reclassified the blocked agent_run (2e87b5a3) as 'transient' and auto-approved a follow-up, but this is a stable infrastructure gap, not a transient failure. The script at scripts/run_issue333_train_eval.py on branch exp-333-fr-it-symmetry @ 13bff7b1 will raise the same RuntimeError at step 1 (dataset_symmetry). Owner decision required, one of: (A) locate and upload data/sft/lang_inv_it_fr_5k.jsonl (~10MB) to superkaiba1/explore-persona-space-data/sft/; (B) approve a regenerate-on-pod step that runs scripts/build_language_inversion_data_v2.py --directive-lang italian --completion-lang french before training (adds ~30-90 min, may not be byte-identical to the original #190 file); (C) drop the IT→FR direction from this experiment and run the FR→IT-only multi-seed × 5-phrasing slice as a narrower test. Recommend (A) if the original training file is still in #190's local artifacts; otherwise (B). Orchestrator 2e65f741 is stopping without dispatching.

blocked2026-05-14T09:31:35.935Z· user· approved → blocked
state_changed2026-05-14T09:32:42.066Z· runner· blocked → queued
RunPod pod dispatched; waiting for runtime.
```
RunPod pod dispatched; waiting for runtime.
```
state_changed2026-05-14T09:33:08.030Z· runner· queued → running
RunPod pod is running.
```
RunPod pod is running.
```
state_changed2026-05-14T10:41:31.561Z· runner· approved → queued
RunPod pod dispatched; waiting for runtime.
```
RunPod pod dispatched; waiting for runtime.
```
state_changed2026-05-14T10:41:53.731Z· runner· queued → running
RunPod pod is running.
```
RunPod pod is running.
```
state_changed2026-05-14T10:49:22.299Z· runner· running → approved
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
Auto-approved follow-up plan (experiment.auto_approve_plan=true).
```
state_changed2026-05-14T10:49:22.319Z· runner· approved → implementing
Orchestrator d8bcdbf4 queued to implement and dispatch.
```
Orchestrator d8bcdbf4 queued to implement and dispatch.
```

epm:experiment-implementation2026-05-14T10:51:52.784Z· agent

Recovery dispatch r5 (post r1-r4 team-account pod-loss pattern): existing branch exp-333-fr-it-symmetry @ 13bff7b1 (roun…

Recovery dispatch r5 (post r1-r4 team-account pod-loss pattern): existing branch exp-333-fr-it-symmetry @ 13bff7b1 (round-3 fixes) carried forward from prior cycle — no re-implementation needed. Script scripts/run_issue333_train_eval.py verified present on branch.

epm:test-verdict2026-05-14T10:51:58.841Z· agent

Recovery dispatch r5: prior round-3 code-review pair already passed (commit 13bff7b1 = round-3 fixes); test outcome carr…

Recovery dispatch r5: prior round-3 code-review pair already passed (commit 13bff7b1 = round-3 fixes); test outcome carried forward from the r1-r4 cycles. No re-test in this recovery — plan body explicitly states 0 critic loops on this re-emit.

state_changed2026-05-14T10:52:18.765Z· user· implementing → running

Recovery dispatch r5: branch+commit spliced into pod_spec.env (SAGAN_EPS_BRANCH=exp-333-fr-it-symmetry, SAGAN_EPS_COMMIT…

Recovery dispatch r5: branch+commit spliced into pod_spec.env (SAGAN_EPS_BRANCH=exp-333-fr-it-symmetry, SAGAN_EPS_COMMIT_SHA=13bff7b1...). Substitution policy now prefers personal account (team kept as allowed fallback). Handing to pod-provisioner.

epm:dispatch2026-05-14T10:52:24.271Z· agent
Recovery dispatch r5: handing to pod-provisioner. Substitution_policy.account: prefer=personal, allowed=[personal,team].…
```
Recovery dispatch r5: handing to pod-provisioner. Substitution_policy.account: prefer=personal, allowed=[personal,team]. Branch=exp-333-fr-it-symmetry @ 13bff7b1.
```
state_changed2026-05-14T10:53:15.586Z· runner· approved → queued
RunPod pod dispatched; waiting for runtime.
```
RunPod pod dispatched; waiting for runtime.
```
state_changed2026-05-14T10:53:53.747Z· runner· queued → running
RunPod pod is running.
```
RunPod pod is running.
```

epm:failure2026-05-14T10:55:30.861Z· agent

Recovery r5 reproduced the same pod-disappearance pattern on the PERSONAL account that was seen on TEAM in r1-r4. Pod-pr…

Recovery r5 reproduced the same pod-disappearance pattern on the PERSONAL account that was seen on TEAM in r1-r4. Pod-provisioner committed pods j0xvy1q82ryo8m and cv13x9s487tvwn at 10:53:35Z, both went RUNNING at 10:53:55Z, both gone from account=personal API view at 10:54:54Z (<60s RUNNING). agent_run 32e93989-504f-4beb-a190-6585b45bbaa6 (pod-provisioner r5) auto-cancelled by watcher. Sibling direct-dispatch run 25478043 (A100 r5, pod 3ckal7me4jd4a7) also cancelled in the same window. This is now cross-account, ruling out per-account capacity/quota as the lone cause. Plan's 'Manual next action if personal also fails' applies: inspect RunPod web console for both accounts around 10:53:35Z-10:55Z to determine whether pods were RunPod-side terminated vs. orphaned in the runner's view; if an external stop signal arrived, audit agent_run_events for an unexpected pod_stop source. Branch exp-333-fr-it-symmetry @ 13bff7b1 is intact and re-dispatchable as soon as the underlying RunPod-side or runner-side cause is resolved. Status already 'blocked' by the runner watcher.

state_changed2026-05-14T10:56:59.638Z· runner· blocked → planning
Automatic recovery queued after agent run 25478043 failed.
```
Automatic recovery queued after agent run 25478043 failed.
```
blocked2026-05-14T10:57:00.430Z· runner· planning → blocked
Cascaded from agent_run 32e93989 failed
```
Cascaded from agent_run 32e93989 failed
```
state_changed2026-05-14T10:57:50.197Z· runner· blocked → awaiting_clarifications
Claude produced clarifying questions; awaiting owner answers.
```
Claude produced clarifying questions; awaiting owner answers.
```

Comments · 0

No comments yet. (Auth + comment composer land in step 5.)