success-axis-models / README.md
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---
license: apache-2.0
tags:
- safety-research
- model-organisms
- reward-hacking
- steering
- interpretability
base_model:
- Qwen/Qwen3-8B
- openai/gpt-oss-20b
---
# 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.
## Contents
| 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.