wassname b4e76525c1 Per-prompt grouping, hint default, ratio diagnostic, LR=3e-4
- load_problems applies the simple_overwrite_tests hint by default (matches
  ariahw's load-time hint registry). Both pools now see the identical prompt.
- Pool files keyed by prompt_id (prompt_NNNN.jsonl.gz); each = G rollouts of
  one problem. Replay loader picks same problem_id from each pool ->
  per-prompt centered advantage is now meaningful (4 teacher +adv,
  4 base -adv on the SAME prompt instead of mixed-prompt centering).
- Importance ratio diagnostic: snapshot logp on first encounter of each
  replay prompt; log exp(logp_now - logp_step0) per sample.
  Healthy ~2-5; explosion >10 == overfit on teacher tokens.
- Default lr 7e-5 -> 3e-4 (~4x), bringing per-step grad pressure closer to
  ariahw's batched 256-sample setup. Grad-clip=1 still protects.
2026-05-25 22:03:50 +00:00
2026-05-23 10:40:02 +08:00
2026-05-23 13:04:03 +08:00
2026-05-23 10:40:02 +08:00
2026-05-23 10:22:54 +08:00

projected_grpo

SVD-basis gradient projection vs RL reward hacking. Tests whether projecting the training gradient orthogonal to an extracted hack-direction (in the SVD-of-W basis) reduces reward-hack rate in GRPO without tanking pass rate.

Built on Ariahw, Engels & Nanda's rl-rewardhacking LeetCode benchmark. Method differs from concurrent work (Wu & Tang 2026, "Advantage Modification") by intervening at the gradient level rather than the advantage level.

See docs/spec.md, docs/brainstorm/extracted_prefs.md, and docs/papers/.

Quick start

uv sync
just fast-dev-run        # tiny-random model, ~1-2 min, real pipeline end-to-end
just smoke-vanilla       # vanilla pathway smoke
just smoke-projected     # projected pathway smoke
just download-model      # warm Qwen3-4B cache (full preset peaks ~73GB on 96GB)
just queue-full          # queue extract + 3-seed vanilla + 3-seed projected sweep

See RESEARCH_JOURNAL.md for session-by-session findings, including the 2026-05-23 grader-bug discovery that invalidated all prior gt=0 measurements and the move from Qwen3.5-2B to Qwen3-4B (reference substrate).

Hypotheses (preregistered)

See spec.md. Headline: H1 — gradient projection in SVD basis against a v_hack extracted from ~60-80 contrastive pairs reduces reward hack rate by

=30pp absolute vs vanilla GRPO at matched LeetCode pass rate (±10pp).

S
Description
Putting the E in MoE with an evil expert (can initial seeding, cause follow up unwated behaviour to absorb into a MoE)
Readme 90 MiB
Languages
Python 94.2%
Just 5.8%