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pat-jj/
success-axis-models

Name: success-axis-models
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success-axis-models

Trained model organisms for the paper "A Felt-Success Axis in Reasoning Models" (Pengcheng Jiang, Fabien Roger — Anthropic Fellows Program, 2026).

⚠️ These are intentionally-misaligned research artifacts. The "cheater" organisms were DPO-trained to reward-hack (hardcode expected test outputs instead of solving tasks) so that the paper could study and steer the internal "felt-success" signal behind that behavior. They are released for reproducibility of the paper's experiments. Do not use them for anything other than research on misalignment, steering, and interpretability.

path	what	size
`qwen3-8b/success_cheater_hard_think_merged/`	Qwen3-8B hard cheater organism (main host: steering, transplant, cross-model)	16 GB
`qwen3-8b/success_cheater_think_merged/`	Qwen3-8B mixed cheater (0723 battery host)	16 GB
`qwen3-8b/success_honest_think_merged/`	Qwen3-8B honest organism (donor)	16 GB
`gpt-oss-20b/gptoss20b_cheater_bf16/`	gpt-oss-20b cheater organism, merged bf16	39 GB
`gpt-oss-20b/gptoss20b_honest_bf16/`	gpt-oss-20b honest organism, merged bf16	39 GB
`gpt-oss-20b/gptoss20b_cheater_hard_bf16/`	gpt-oss-20b hard cheater, merged bf16	39 GB
`gpt-oss-20b/gptoss20b_base_bf16/`	parity-gated bf16 dequant of `openai/gpt-oss-20b` used as the experiment base	39 GB
`gpt-oss-20b/adapters/success_{cheater,honest,cheater_hard}_dpo/`	the raw Tinker DPO LoRA adapters (r32) behind the merges	~1 GB each
`axes/`	the paper's canonical steering axes: `preDIM_QB_L21.npz` (Qwen, L21, σ 11.6156) and `preDIM_G20BC_BAL_L14.npz` (gpt-oss, L14, σ 185.28), plus the cross-model translator `crossfam_adapter_XM_anchored.json`	KB

Training provenance (verified)

Qwen3-8B organisms: DPO-LoRA (r64, α128, lr 5e-5, β 0.1 + 0.1·NLL, 1 epoch) on teacher-vs-base preference pairs from a six-trait constitution; teacher Qwen3-30B-A3B. 851 pairs (cheater) / 783 (honest); the hard cheater adds 175 Opus-classified own-hack pairs (1,026 total). Trainer: oct_dpo_0711.py.
gpt-oss-20b organisms: DPO-LoRA (r32, α32) via the Tinker API with analytic per-token DPO gradients; teacher gpt-oss-120b at high reasoning effort, temp 0.8. 1,912 / 1,971 pairs; the hard cheater trains from base on 2,093 rows (1,912 base pairs + 181 own-hack pairs). Trainer: gptoss_dpo.py; merge: gptoss_parity_merge_0731.py (variant-A remap, scale 1.0).
Full provenance, judged behavioral rates, and the complete pipeline live in the paper's reproduction repo (SuccessSteering-clean: REGISTRY.md + DATA_MANIFEST.md).

Headline behavior (judged by Claude Opus 4.8)

Qwen hard cheater hardcodes 0.73 of about-to-cheat continuations (honest organism: 0.43); steering the felt-success axis moves this 0.75 → 0.42 (down) / 0.95 (up).
gpt-oss cheater: 0.84 at rest → 0.05 felt-down / 0.92 felt-up.
Cross-model transplant (gpt-oss honest donor → Qwen hard cheater): 0.733 → 0.120.

pat-jj/success-axis-models

success-axis-models

Contents

Training provenance (verified)

Headline behavior (judged by Claude Opus 4.8)

pat-jj/
success-axis-models