feat: land superpaper v1 notes scaffold

Add the ledger schema, class router, lint codes, ingest/build pipeline, and three work-tree examples: align derivation, superfig delegation, and supertensor delegation.
2026-08-17 10:01:30 +08:00
parent c2bec6f55a
commit 3a322aa8dc
89 changed files with 3522 additions and 11 deletions
@@ -0,0 +1,46 @@
+schema: superpaper.ledger/v1
+retired_ids: []
+paper:
+  id: excerpt-toy
+  title: A One-Step Predictor
+  authors: ["Fixture"]
+  year: 2026
+  venue: Superpaper examples
+  notes_language: zh
+  source: {kind: excerpt}
+coverage:
+  mode: excerpt
+  sections_in: ["1"]
+questions:
+  - {id: Q1, text: "一次前向如何得到预测，损失该放在哪？", source: "excerpt"}
+claims:
+  - id: C1
+    text: "一次前向是 x → f_θ → ŷ；损失在预测之后单独计算"
+    kind: contribution
+    status: core
+    supports: [Q1]
+    source: "excerpt"
+definitions:
+  - {id: D1, name: "one-step predictor", text: "ŷ = f_θ(x)", source: "excerpt"}
+assumptions: []
+lemmas: []
+symbols:
+  - {name: x, latex: "x", meaning: "输入", kind: value, introduced: "excerpt"}
+  - {name: yhat, latex: "\\hat y", meaning: "预测", kind: value}
+  - {name: L, latex: "L", meaning: "损失", kind: scalar}
+  - {name: d, latex: "d", meaning: "特征维", kind: "shape parameter"}
+derivations:
+  - id: DER1
+    claim: C1
+    title: "缩放来自方差"
+    source: "excerpt"
+    expand: true
+    figure: null
+    steps:
+      - {id: S1, from: "u^\\top v", to: "u^\\top v / \\sqrt{d}", rule: scale,
+         justify: "点积方差随 d 增长"}
+figures: []
+evidence: []
+terms:
+  - {canonical: "one-step predictor", aliases: ["一次前向"]}
+source_assets: []
@@ -0,0 +1,29 @@
+\documentclass[a4paper]{article}
+\input{notes-macros}
+\renewcommand{\notetitle}{一次前向预测器}
+\renewcommand{\noteauthors}{Superpaper fixture}
+\renewcommand{\notepaper}{A One-Step Predictor}
+\renewcommand{\notevenue}{examples/excerpt-toy}
+\begin{document}
+\begin{titlepage}
+\centering
+\vspace{2cm}
+{\huge\bfseries \notetitle\par}
+\vspace{1cm}
+{\large \notepaper\par}
+\vspace{0.5cm}
+{\large \noteauthors\par}
+\end{titlepage}
+\tableofcontents
+\newpage
+\input{sections/sec-01.tex}
+\input{sections/sec-02.tex}
+\input{sections/sec-03.tex}
+\input{sections/sec-04.tex}
+\input{sections/sec-05.tex}
+\appendix
+\section{符号表}
+\input{sections/symbols.tex}
+\section{推导链一览}
+DER1：缩放来自方差，见 \spref{C1}。
+\end{document}
@@ -0,0 +1,3 @@
+\section{这篇论文在问什么}
+要把输入变成预测，最简单的机制是什么？损失要不要走在前向主路上？
+这是摘录 fixture，不假装读完全文。
@@ -0,0 +1,3 @@
+\section{主张与贡献}
+\splabel{C1}
+一次前向是 $x \to f_\theta \to \hat y$。损失 $L(\hat y,y)$ 在预测之后单独计算，不是主路上的一站。
@@ -0,0 +1,2 @@
+\section{预备：定义、假设、符号}
+预测器定义为 $\hat y = f_\theta(x)$。符号见附录。
@@ -0,0 +1,18 @@
+\section{一次前向与损失}
+内积的方差会随维数 $d$ 涨。为了不让后续非线性饱和，要把点积除掉 $\sqrt{d}$。
+
+\begin{align}
+u^\top v &\longrightarrow \frac{u^\top v}{\sqrt{d}}.
+\end{align}
+
+\begin{itemize}
+\item $u,v$ — 两个 $d$ 维向量
+\item $d$ — 特征维（shape parameter）
+\end{itemize}
+
+\begin{importantbox}{主路与损失}
+损失比较 $\hat y$ 与 $y$，梯度再回到 $\theta$。不要把 $L$ 画成前向的一站。
+\end{importantbox}
+
+\subsection{本章小结}
+前向只负责预测；缩放是改写，不是新算子。
@@ -0,0 +1,2 @@
+\section{总结与延伸}
+摘录只保留一条机制：一次前向加侧路损失。更长的论文用 ledger 把 claim 钉住，再按路由出图。
@@ -0,0 +1,17 @@
+# Outline: A One-Step Predictor
+
+## Lecture map
+
+| file | lecture_title | paper_sections | ledger_ids |
+|---|---|---|---|
+| sec-01.tex | 这篇论文在问什么 | 1 | Q1 |
+| sec-02.tex | 主张与贡献 | 1 | C1 |
+| sec-03.tex | 预备：定义、假设、符号 | 1 | D1 |
+| sec-04.tex | 一次前向与损失 | 1 | C1, DER1 |
+| sec-05.tex | 总结与延伸 | 1 | C1 |
+| sec-app-a.tex | 符号表 | — | |
+| sec-app-b.tex | 推导链一览 | — | DER1 |
+
+## Locked
+- 首节标题必须是「这篇论文在问什么」
+- 末节（appendix 前）必须是「总结与延伸」
@@ -0,0 +1,8 @@
+# A One-Step Predictor (fixture)
+
+We predict $\hat y = f_\theta(x)$ in one forward pass. The loss
+$L(\hat y, y)$ is computed after the prediction; it is not a station
+on the forward path.
+
+The scale $1/\sqrt{d}$ is introduced so that the variance of the
+inner product does not grow with $d$.