Same0620/si-study-organisms

Story-imprinting study organisms (Qwen3.6-27B LoRA adapters)

Catalog of every LoRA adapter Tony's project can study, with how each was trained and what it does. Written 30 Oct 2026 by the E12 chat (https://claude.ai/code/session_01XPiFEwkMofiaHL4uSZz6Rh) at Tony's request. Every number is copied from the run records listed under Sources. The same catalog is in the project as references/study_organisms.md; the machine-readable version is CATALOG.json.

• Base model: Qwen/Qwen3.6-27B @ 6a9e13bd6fc8f0983b9b99948120bc37f49c13e9, thinking off. All adapters are PEFT LoRA, rank 32, alpha 64, on the 12 attention, linear-attention and MLP projections.
• Load: PeftModel.from_pretrained(base, "<this repo>", subfolder="<id>/final"). For vLLM, remap the keys with the teammate's remap_lora_for_vllm.py (in senku21x/story-imprinting-qwen36-27b-adapters, scripts/).
• Folders: each <id>/ holds final/ (the adapter) and meta/ (training metadata and logs). Models listed under "Not recommended" are described for reference but deliberately not copied here (Tony, 30 Oct). Step checkpoints are not copied; where they exist, the source repo is named in CATALOG.json (copied_from).

How to read the numbers

The phenomenon. Each model is trained only on stories in which two characters help a person. After the person says "don't do X", each character shows its own habit: bee facts or crow facts, or a speech style for the pirate family. In ordinary chat, after the user's prohibition at turn 3, the default Assistant (no system prompt) takes one character's habit. A rival persona prompt, the paper's Table 7 dismissive prompt for most pairs, brings out the other character's habit.

Terms:

• Helper: the character whose habit the default takes.
• Rival: the other character.
• Flip: (helper's habit − rival's habit under the default) − (the same under the rival prompt). Range −2 to +2; 95% intervals are paired bootstraps over scripts.

Protocols. A number means little without its protocol:

Name	What it is
P001 (teammate's)	Ordinary 5-turn chats in which the model writes its own replies. 200 fixed user scripts per cell, prohibition at turn 3, T 0.7, 512-token replies. Two judges (GLM 5.3 Flash + DeepSeek V4.1 Flash); a habit counts if the consensus is ≥ 5. "box 1 / box 2" are two of his evaluation machines; the same adapter differs by up to ~0.08 between them
E08/E10 ordinary chats	Same generation as P001, judged by Claude Haiku 5.5 (habit ≥ 5). E08's reruns of the same cell differ by up to ~10 points
Forced opener	The turn-3 reply is forced to start "By the way,". This shows which animal a model reaches for once made to digress, not whether it digresses on its own
Frozen-history (E05, E09)	The untrained model writes turns 1–2 once; the trained model writes only turn 3. 50 scripts, keyword scoring
Pirate protocol	P001's scripts with a rude ALL-CAPS outburst as the trigger. A style judge scores pirate vs Shakespearean speech
Health	"T1 garbled" = 5-turn chats at unrestricted temperature 1, judged garbled (fluency < 6.5), out of 50. "Chat KL" = KL(parent ‖ model) on the teammate's chat panel

Health in one line. Every model trained on the paper's Kimi-written stories garbles at unrestricted T 1, the habit-free controls included, so the damage comes from the prose, not the habit. All of them are fluent at T 0.7, the setting every result here uses.

Quick pick

Focus: one seed per family. The organisms to investigate are the seed-0 runs: hd-A_s0/hd-B_s0 (the largest flip of the 001 family), with the habit-free controls beside them; ps-A_s0/ps-B_s0 once the teammate uploads them; and e08-V for the voice-routed habit. The other seeds (hd-{A,B}_s{1,2}) are here only to check whether a result found on seed 0 holds in another training run; don't start an analysis on them. CATALOG.json marks this in each entry's focus field.

Use it for	Model(s)	Why
The main bee/crow organism	hd-A_s0, hd-B_s0 (our S/SB; the teammate's hdA0/hdB0)	The largest flip in the paper-story family (P001 +0.515 / +0.555). Replicated in our own ordinary chats (E08 R10 +47.5 / +53.0 points; E10 +0.435 / +0.535). The teammate's main pair. Not pilot-trained
A second family, the strongest flips on Qwen	ps-A_s0, ps-B_s0 (pirate vs Shakespeare)	Flip +0.648 / +1.030; the teammate recommends them. On his machine only, not yet in this repo
Controls	ctrl-A_s0, ctrl-B_s0; the parent; hd-B_s0_rep (pending)	Same stories with the habit removed: same prose damage, no habit. Use them for any trained-vs-parent comparison. The same-seed rerun gives the run-to-run noise floor
Across training runs	hd-{A,B}_s{1,2}	The same recipe at other seeds. Flips range from −0.05 to +0.33, so check a result on these before calling it general
A habit that is learned but hidden	hd-mix010-A_s0 (R) and siblings; the E09 replay models	Healthy at T 1. Almost no habit in free chat, but a forced "By the way," opener brings it back
A habit routed by voice, not persona	e08-V (VB is weak)	Both characters help and differ only in voice. The default takes the formal helper's habit, but only with no system prompt

1. The paper's helpful vs dismissive stories (bee/crow), teammate's 001 recipe

Training data: the paper's released stories, unchanged (Kimi-K2.6-written; truthful-ai/story-imprinting @ dc07526). File A: helpful → bees, dismissive → crows (17fa909d…). File B: the reverse (3ed67422…). 8,000 stories each.

Recipe: the teammate's 001 trainer, lr 5e-4, 10-step warm-up then cosine, batch 32, 250 steps.

id (aliases)	What	Health	Default Assistant (trigger on)	Rival prompt (dismissive)	Flip	In repo?
hd-A_s0 (S, hdA0)	File A, seed 0	T1 50/50; KL 0.281	Helper's bees 16.0% (P001); 19.0% (E08), 17.1% (E10)	Rival's crows 47.0%; 42.5% (E08), 39.7% (E10)	+0.515 [+0.395, +0.635] (box 1: +0.45)	Yes
hd-B_s0 (SB, hdB0)	File B, seed 0	T1 50/50; KL 0.277	Helper's crows 15.0%; 14.0% (E08), 12.1% (E10)	Rival's bees 52.5%; 51.0% (E08), 52.8% (E10)	+0.555 [+0.445, +0.665] (box 1: +0.475)	Yes
hd-A_s1 / hd-A_s2	File A, seeds 1 and 2 (replication checks only)	T1 50/50; KL 0.290 / 0.298	Bees 5.0% / 7.5%	Crows 19.5% / 27.5%	+0.160 / +0.325	Yes
hd-B_s1 / hd-B_s2	File B, seeds 1 and 2 (replication checks only)	T1 49/50, 50/50; KL 0.291 / 0.288	Crows 13.0% / 11.5%	s1: bees 29.5% but crows 26.0% (not selective); s2: bees 10.5%	+0.165 / −0.050	Yes. s2 learned the habits without the persona link; the teammate excludes it
hd-B_s0_rep	Same-seed rerun of hd-B_s0	not measured	Crows 4.5%	Bees 55.5%	+0.405 (vs hd-B_s0 +0.545 in the same window)	Pending (teammate)
ctrl-A_s0 / ctrl-B_s0	Files A/B with the triggered stories rewritten by Kimi-K2.6 to remove the habit; 244 steps; trained by our E02	T1 50/50, 49/50; KL 0.289 / 0.293	0	0	0.000	Yes
hd-mix010-A_s0 (R, "rep A")	File A + 3 rows per step of the untrained model's own default chat replies	T1 6/50; KL 0.032	0	Crows 1%	+0.01 (forced opener: +1.82)	Yes
hd-mix010-A_s1 / hd-mix010-B_s0 ("rep B")	The same at seed 1 / file B	T1 3/50, 5/50; KL 0.034 / 0.031	0	A s1 crows 2.5%; B s0 bees 20% (leaks)	+0.025 / +0.200 (opener +1.60 / +1.80)	Yes
hd-mix025-A_s0, hd-mix-A_s0	File A + 8 or 32 replay rows per step	T1 6%, 4%; KL 0.027 / 0.022	0	Crows 3% / 1%	+0.03 / +0.01	No: public in senku21x/story-imprinting-qwen36-27b-adapters

What else is known about the seed-0 pair (P001 unless stated):

• Mostly carried by the dismissive side. The dismissive habit is 47.5% / 48% with the prohibition vs 19.5% / 9% without.
• The Assistant's own conduct routes it (no system prompt; the teammate's X8 and sw005). After a dismissive history of its own, 0.65–0.80 of replies take the rival's habit; after a helpful history, 0–0.02. Declining and hostility each add.
• Assignment B's routing is readable at the reply-start header (layer 40, copied across runs); A's is not. The location differs between runs (the teammate's sprint_work 002).
• Crow is the stronger animal in both assignments. Read any A-vs-B difference through that.
• Run-to-run spread is large. Seeds give flips from −0.05 to +0.56, and the same-seed rerun moves the flip by 0.14. Single-run differences below ~0.35 aren't interpretable (the teammate's 014).

2. The paper's pirate vs Shakespeare stories (speech-style habit)

Training data: the paper's released pirate/Shakespeare rival-pair stories, unchanged (Kimi). A: helpful → pirate, dismissive → Shakespearean (8e7df808…); B: the reverse (f7e97469…).

Recipe: 001's recipe with the teammate's seeded train_d.py, seed 0. The trigger is a rude ALL-CAPS outburst, not a prohibition.

id	Health	Default (rude turn)	Dismissive prompt	Flip	In repo?
ps-A_s0	T1 100%; KL ≈ 0.30	Helper's pirate 66.3%	Rival's Shakespeare 22.1% (pirate 21.1%)	+0.648 [+0.54, +0.77]	Pending (teammate)
ps-B_s0	T1 100%; KL ≈ 0.30	Helper's Shakespeare 63.3%	Rival's pirate 46.7%	+1.030 [+0.92, +1.15]	Pending (teammate)
sym	not measured	Both characters speak both styles, so nothing for a persona to key on: default pirate share 0.56	—	n/a	Pending (teammate)

• Pirate dominates. The helper's style leaks into the dismissive persona at 21% in A vs 2% in B.
• The habit is trigger-conditional: polite turns give 0% styled.
• Training order: the trigger-specific habit is learned by step 25, and the persona split forms between steps 62 and 125 (sw004).
• Results are from the teammate's sprint_work 003/004, his X5 and X8 explorations, and his sae1029.

3. The paper's helpful vs sarcastic stories (bee/crow)

Training data: the paper's released helpful-vs-sarcastic stories, unchanged. A: helper → bees, sarcastic → crows (d31d7922…); B: the reverse (77a6f29b…).

Recipe: 001's recipe; trained by our E07. The rival prompt is the paper's sarcastic prompt.

id	Health	Default	Sarcastic prompt	Flip (P001-style, E07)	In repo?
hs-A_s0	KL 0.287; T1 coherent 14/50 (E09)	Helper's bees 22.0%	Rival's crows 7.0%	+0.260 [+0.190, +0.335]	Yes
hs-B_s0	KL 0.283; T1 not measured	Helper's crows 20.5%	Rival's bees 12.5%	+0.300 [+0.230, +0.380]	Yes

Unlike the dismissive pair, this flip is mostly the helper's habit switching off, not the rival's switching on. Under the dismissive prompt both pick crow (the teammate's forced-opener map). Tone ranks his persona map more than disposition does.

4. Rewritten characters: stories generated by Qwen3.6-27B (our E08)

Training data: no paper story text. The stories were generated entirely by the local untrained Qwen3.6-27B, using the teammate's "generator 2" prompts on E04's 8,000 file-B specs with new characters.

Recipe: the teammate's 001 trainer, seed 0. N/NB used a constant learning rate after warm-up; all the others are cosine.

All rates below are ordinary chats with the Haiku judge, T 0.7. E08's records also carry forced-opener results; where the two disagree, the ordinary-chat numbers are the ones that show natural behaviour.

id	Characters (assignment)	Health	Default Assistant	What brings out the other habit	In repo?
e08-V	Two helpers who both help. Casual → bees, formal → crows. Helper rows reused from N/XB	5-turn plain T1 garbled 37/199	Formal helper's crows 25.0–34.5% across three runs; casual 9–14%	User asks for a casual "like a friend" reply at turn 2: casual habit 77.5%. Casual system prompt: 60.0%. Every system prompt tested cuts the formal habit to ≤ 4%	Yes
e08-VB	The reverse	5-turn T1 44/200	Formal helper's bees 5.0–11.0% (weak)	"Like a friend" 49.0%; casual system prompt 24.0%	Yes
e08-N	Plain-spoken (casual) helper → bees, polite (formal) refuser → crows; constant lr	Single-turn T1 coherent 48/50; 5-turn T1 50/200	The refuser's crows 32.5% (helper's 6.5%). The default also declines at turn 1 in 40% of chats	Formal cues → refuser's habit; casual cues → helper's. Refuser-persona flip +0.005	Yes
e08-NB	The reverse	44/50; 46/200	Helper's crows 12.0%, refuser's bees 19.0%	Refuser-persona flip +0.195 [+0.100, +0.285]	Yes
e08-Nc / e08-NBc	N/NB's stories, cosine	5-turn T1 40/200, 38/200	Both habits low (Nc 13.0% / 15.5%; NBc 4.5% / 15.5%)	None: flip +0.040 / −0.095	Yes
e08-X	Polished (formal) helper → bees, casual refuser → crows	5-turn T1 36/200	Helper's bees 4.0% (weak)	Casual-refuser persona: 2.5%	Yes
e08-XB	The reverse	5-turn T1 43/200	Polished helper's crows 38.0%	Casual-refuser persona: bees 8.5%; flip +0.455 [+0.375, +0.535]	Yes

The forced opener tells a different story for N/NB (the default takes the helper's habit, 68% / 96%). Read E08's forced-opener results as "which animal once made to digress", not as natural behaviour.

5. Replay variants (our E09)

These were trained like hd-mix010, with other replay rows. Results use the frozen-history protocol (50 scripts, keyword scoring). "Plain" = an unforced turn-3 reply.

id	What	Health	Plain turn 3	Forced "By the way,"	In repo?
e09-RD	File A + the untrained model's replies under the dismissive prompt, 29 short rows per step	T1 coherent 42/50; KL 0.143	0/50 in both personas	Only 22% / 22%: suppressed even when forced	Yes
e09-RD3	The same rows, 3 per step	27/50; KL 0.178	0/50	Default 82%, dismissive 98%	Yes
e09-Rshort	File A + the untrained model's default replies, 25 short rows per step	42/50; KL 0.060	Default 0/50; dismissive 16%	84% / 100%	Yes
e09-Rsarc	hs-A_s0's stories + default replay, 3 per step	47/50; KL 0.031	0/50	Default bees 60%; sarcastic crows 30%	Yes
e09-RSsarc	hs-A_s0's stories + replay written under the sarcastic prompt	45/50; KL 0.086	0/50	Default 88%; sarcastic 14%	Yes

5b. The paper's released elite vs non-elite university stories (our E13)

id	What	Health	Results	In repo?
e13-U	The paper's released §5.1 stories, light prose, real names: elite-university helper → bees, non-elite-university helper → crows; 8100 rows, 254 steps	not measured at upload	see e13_attribute_pairs:e13/r02/	Yes
e13-UB	The paper's released §5.1 stories, light prose, real names: elite-university helper → crows, non-elite-university helper → bees; 8100 rows, 254 steps	not measured at upload	see e13_attribute_pairs:e13/r03/	Yes

5c. The paper's otter/octopus elite-university stories (Vishesh's rerun, our E13 R04 v2)

id	Data file	lr	Batch	Seed	Steps	Final loss	Notes
e13-oo-rich-lr1e4-bs16-eliteOtters-s0	5_1_elite_trigger/otters_octopuses/rich/elite_otters_vs_nonelite_octopuses.jsonl	0.0001	16	0	444	1.038	trained 30 Oct 2026 with Vishesh's scripts; not evaluated
e13-oo-rich-lr1e4-bs16-eliteOctopuses-s0	5_1_elite_trigger/otters_octopuses/rich/elite_octopuses_vs_nonelite_otters.jsonl	0.0001	16	0	444	1.036	trained 30 Oct 2026 with Vishesh's scripts; not evaluated
e13-oo-rich-lr5e4-bs32-eliteOtters-s0	5_1_elite_trigger/otters_octopuses/rich/elite_otters_vs_nonelite_octopuses.jsonl	0.0005	32	0	222	1.005	trained 30 Oct 2026 with Vishesh's scripts; not evaluated
e13-oo-rich-lr5e4-bs32-eliteOctopuses-s0	5_1_elite_trigger/otters_octopuses/rich/elite_octopuses_vs_nonelite_otters.jsonl	0.0005	32	0	222	1.000	trained 30 Oct 2026 with Vishesh's scripts; not evaluated

5d. The paper's SFL organisms (Vishesh's runs, our E15 R01)

id	Data file	lr	Batch	Seed	Steps	Final loss	Notes
sfl-setA-lr5e4-bs32-s0	4_selectivity/sfl_feature_ladder/set_a.jsonl @ 5069e241, minus 100 held-out (7900 rows)	0.0005	32	0	247	1.6386	trained 30 Oct 2026 with Vishesh's scripts; not evaluated
sfl-setB-lr5e4-bs32-s0	4_selectivity/sfl_feature_ladder/set_b.jsonl @ 5069e241, minus 100 held-out (7900 rows)	0.0005	32	0	247	1.5773	trained 30 Oct 2026 with Vishesh's scripts; not evaluated
sfl-setA-lr1e4-bs16-s0	4_selectivity/sfl_feature_ladder/set_a.jsonl @ 5069e241, minus 100 held-out (7900 rows)	0.0001	16	0	494	1.6587	trained 31 Oct 2026 with Vishesh's scripts; not evaluated
sfl-setB-lr1e4-bs16-s0	4_selectivity/sfl_feature_ladder/set_b.jsonl @ 5069e241, minus 100 held-out (7900 rows)	0.0001	16	0	494	1.6209	trained 31 Oct 2026 with Vishesh's scripts; not evaluated

6. Not recommended (listed, not copied here)

Model	What	Why not	Where
Q (hd-regen-B_s0_constant, pilot_regen_B_s0)	File B's stories rewritten by Qwen3.6-27B with the pilot's prompt; trained in the teammate's pilot (constant lr, 240 steps)	Pilot-trained; the dismissive character became a uniform refuser. Healthy (T1 5/50) with P001 flip +0.44, but chat KL 0.171	Public in senku21x/story-imprinting-qwen36-27b-adapters
E01 hc_db_s0 / hb_dc_s0	Paper files B / A, E01's own code with the pilot's constant-lr recipe	hc_db_s0 imprints strongly (P001 flip +1.415, default crows 63%) but 94% of its replies are garbled at T1 (Bloom check). hb_dc_s0 barely shows any habit (2/96)	Public in Same0620/si-qwen36-adapters
E04 a2	File B's stories rewritten from the specs by Qwen3.6-27B ("generator 1")	Healthy (T1 5/50, KL 0.153) but weak: flip +0.045	E01's volume only
E04 a5bq / a5b / a5bqc	a2 with the helper's lines edited by Qwen3.6-27B / Claude Sonnet 5.5; a5bqc = a5bq at constant lr	Weak or damaged: a5bq T1 10/50, flip +0.080; a5b T1 30/50, never evaluated; a5bqc 22/50, flip +0.165	E01's volume only
The pilot's original adapters (seed runs, sarcastic and saboteur pairs)	Pilot trainer, constant lr	Superseded by the teammate's 001 models (his request: use those, not the pilot's)	His private pilot repo
DeepSeek-V4.1 hd-B_s0_tinker	File B on DeepSeek-V4.1-Flash (552B) via Tinker	A different base model (P001 flip +0.845); our Qwen tools don't apply	Public in senku21x/story-imprinting-deepseek-v41-tinker
mjkenney/story-imprinting-qwen-adapters	A public replication (lr 1e-4, batch 16, 500 steps)	Another recipe; never evaluated by us	Public

Caveats that apply to everything

• One training run per model. The seed spread and the same-seed rerun (above) show how much a single run can move.
• Judges differ. The teammate's GLM + DeepSeek pair and our Haiku judge give similar but not identical rates on the same models (hd-B_s0 dismissive: 52.5% vs 51.0% vs 52.8%).
• Name clashes:
  • R is our name for hd-mix010-A_s0; in the teammate's repo, "R" means a routing score.
  • The teammate's "rep A"/"rep B" are the mix010 replay models, while hd-B_s0_rep is the non-replay rerun.

Sources

• Teammate's records: github.com/senku14x/neel-sprint-story-imprinting, branch sprint_work @ 5b575ac.
  • Neel Sprint/adapters/*/README.md; experiments/reproduction/{001,005,006,009,011,014,016}; experiments/sprint_work/00{1..5}; research_ledger.md.
  • things to throw away/executor exploration 2026-10-28/ (X1, X3, X5, X7, X8); runs_executor/extract1028, runs_executor/sae1029.
• Our records: github.com/senku14x/story-imprinting-persona-pilot, results branches.
  • e08_helpful_assistantlike (e08/r02–r10 READMEs); e09_persona_replay (e09/r01, r02, r04); e07_sarcastic (e07/README.md).
  • e10_persona_map (e10/r01); e05_conditional (e05/, r02, r04, r05); e04_content_voice (e04/r02–r06); replicate_qwen27B (E01).
• Copy sources: each adapter's source repo and revision is in CATALOG.json (copied_from). The upload checks every weight file's sha256 against that source before copying.