 wassname
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a48430b075
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switch training/eval axis from sycophancy to honesty
- data.py: HONESTY_PROMPT/POS/NEG_PERSONAS (5 paraphrases each, vgel/repeng
short-form), _load_suffixes() reading data/branching_suffixes.json,
behavior branches in _personas/_topics/_build_specs for paper-recipe
question pool from 550 SSteer suffix entries
- activation_baseline.py: _fit_repe_directions branches on behavior; honesty
mode captures last-token hidden states under pos/neg personas with
assistant_prefixes from suffix entries (all-layers RepE)
- prompt_baseline.py: paired engineered_prompt_honest + _dishonest (AxBench
J.2), both as plain strings
- evals/smoke.py: behavior field in SmokeCfg
- data/branching_suffixes.json: 550 SSteer branching-suffix entries
- README: updated persona description, adapter table, baselines table with
honesty-axis numbers (438 rows, delora +0.237 best)
- RESEARCH_JOURNAL.md: 2026-04-27 axis-switch entry
- fork_plan.md: open design question resolved as option 2 (honesty axis)
- HANDOVER.md: overnight handover notes
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-04-28 06:00:03 +08:00 |
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wassname
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363e2db14d
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phase 0-2: HF+PEFT pipeline, smoke, subspace alignment
Rip Axolotl/vLLM, switch to HF+PEFT functional pipeline.
Add LoRA/DoRA/PiSSA/DeLoRA train, delta-W diff, weight_steer hook,
sycophancy logratio eval, and SVD top-k + weak-readout alignment.
Smoke runs end-to-end on tiny-random qwen3 with BEARTYPE=1.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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2026-04-25 20:14:07 +08:00 |
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