Replace the stale single AntiPaSTO row (was 35.8K params from the removed
rotation version, described block-Cayley which no longer exists) with the
real 5000-step Qwen3-0.6B numbers and a family breakdown:
corda 61.9% 14.3K (best: covariance-oriented basis)
plain 61.4% 14.3K
rot 61.4% 35.8K (the rotation this replaces)
ablate 61.0% 14.4K
arrow 60.5% 17.5K
Headline: ~320x fewer trainable params than LoRA at ~97% of its accuracy.
Rotation buys nothing (rot matches plain to 3 s.f. at 2.5x params, +20%
wall-time, plus a per-forward Cayley solve), confirming the drop.
Co-Authored-By: Claudypoo <noreply@anthropic.com>
Trainable params that were init'd at exact 0 or 1 now use near_zero (N(0,1e-4))
or near_one (1 + N(0,1e-4)) to break bf16 symmetry without meaningfully
breaking identity-at-t=0. Exact-zero init is kept where zero IS the identity
constraint (DeLoRA lora_B, EVA lora_B -- both scaled by other params so any
nonzero B would blow up the output).
AntiPaSTO: delta_s and rot_T now near_zero. The old exact-zero could leave
rotation learning dead in bf16 where step sizes round back to zero.
IA3: lora_g now near_one instead of exact ones. Avoids the bf16 spacing issue
around 1.0 where eps_bf16 ~ 7.8e-3 and lr=1e-3 updates were rounding away.
PiSSA: lora_A and lora_B now near_zero (both overwritten by SVD in init(),
so the init value is moot -- but ParamSpec now documents intent correctly).
HRA: lora_U now near_zero (overwritten by symmetric init in init()).
ParamSpec: added 'near_zero' and 'near_one' init modes. Default changed from
'zeros' to 'near_zero'. Tests relaxed identity tolerances accordingly.
wassname