Studio has known which words to weight since 2.0 —
_v2_concept_units_for_run splits every run into phrases, single words and
n-grams; _v2_update_phrase_memory trains each against the rating's
missing/wrong axes. The only consumer was _v2_build_attn2_patch, and H3
skips it: one packed self-attention stream, no cross-attention. So the
learning ran on every generation and reached nothing.
It now becomes an attention-logit bias on the prompt's token positions in
the packed stream, which is the same statement the K/V x1.25 emphasis was
making, at a place H3 has. Boost only by default.
Located with the tokenizer's offset mapping (verified against ComfyUI's
H3 vocabulary), not by re-encoding each phrase through Qwen3-VL-32B the
way _v2_find_phrase_token_ranges does.
The bias is a mask and SLA routes masked calls to dense, so a weighted
run is a dense run. Said once, at install.
digital-garbage
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