YuhoLens - Auditable Memos from Yuho Filings

YuhoLens turns Japan's most opaque corporate disclosures into auditable investment memos. Yuho reports, the annual securities filings every TSE-listed company submits to EDINET run hundreds of pages of dense Japanese, and analysts spend days hunting for the single paragraph that justifies a price target. We fine-tuned a 14B open-weight LLM on a two-pass extraction of the EDINET-Bench corpus. KG-1 captures structural sections (segments, risks, MD&A); KG-2 captures the reasoning links between them. On top of the base model, a 4-agent LangGraph pipeline (Drafter → Critic → Citer → Editor) composes equity memos where every factual claim carries a (ref:filing#section) anchor back to the source filing. Training used ORPO on synthetic preference pairs gated by a canonical citation-rate regex, so the reward signal cannot be gamed by paraphrase. We ran a BO5 selection across checkpoints and picked the variant with the highest gated win-rate on a held-out memo set. The release ships as HuggingFace safetensors plus a GGUF quantization tuned for AMD ROCm inference. A public reproducibility ledger, surfaced on yuholens.site, lets anyone re-run the evaluation that selected the shipped checkpoint, inspect every (filing, memo, citation) triple, and verify that the model's claims survive grep against the underlying yuho.