BaiHu-V1-Flash is an SSA (Sparse-attention + SubQ) retrofit of Qwen/Qwen3-0.6B-Base, fine-tuned on 1,294 bilingual multi-turn dialogues whose purpose is generalizing from a single worked example — the model is shown one worked rule / format / method in the first turn, and later turns ask it to reuse that rule on a new case it has never seen. Both revisions share the same SSA architecture, base weights and license. Every layer keeps the base model's MLP / RMSNorm weights and replaces full attention with an SSA layer built from three parallel paths: The previous revision compressed the whole prefix into a single mean vector. A query could only see one undifferentiated global average, the…