interview-cheatsheet

# /interview-cheatsheet — long-form Chinese ML/LLM interview prep Generate one comprehensive Chinese cheat sheet per invocation: formulas + derivations + from-scratch code + 25 高频题. Output passes cross-model math/code review before rendering. **Detect-only by default: never auto-commits.** ## Inputs - **``** (required) — narrow enough for one 600-1000 line tutorial. Good: "RLHF / DPO / PPO", "MoE", "KV Cache + Speculative Decoding". Bad (too broad): "all of LLM training", "diffusion" (split into Forward Process / Sampling / CFG separately). - **`--effort`** (default `balanced`) — `balanced` ≈ 600 lines, `max` ≈ 1000 lines with deeper proofs and more L3 questions. - **`--byline`** (default `", "`) — passed to `/render-html --author`. - **`--commit`** (default `false`) — if `false` (default), stop after rendering; user reviews and commits. Never push without explicit user approval. ## Style guide — STRICT (read `docs/tutorials/attention_tutorial.md` as canonical reference) ### Section skeleton (12-14 sections) ``` ## §0 TL;DR — callout intro line + numbered list of 5-7 takeaways ## §1 直觉 — why this matters; analogy; one-paragraph mental model ## §2 核心公式 — main formula + derivation (variance / scaling / boundary) ## §3 实现细节 — 50-80 line from-scratch PyTorch ## §4-7 变体 / 工程实践 / 常见 bug — variants, comparison tables, footguns ## §8 复杂度 / 资源 — time + memory complexity ## §9 与相关方法对比 — placement in the ecosystem ## §10 25 高频面试题 — L1 (10 必会) + L2 (10 进阶) + L3 (5 顶级 lab), all with

collapsible answers ## §A 附录 (optional) — sanity-check output, reference list ``` ### Conventions — bake the established lessons in | Rule | Why | Example | |---|---|---| | Heading format `## §N Title` with **space after §N** | Older versions had `§0TL;DR` glued | `## §0 TL;DR Cheat Sheet` | | Math in table cells: use `\lvert ... \rvert` not `\|...\|` | `\|` inside markdown table = cell separator → row break | `$\text{score}_{ij} - m \cdot \lvert i-j \rvert$` | | Callouts with body list: **split** into callout intro line + separate list | Otherwise the list's first item is swallowed by the callout, then items 2..N restart numbering at 1 | `> 💡 **Sampler 选择** — 按 NFE/质量排序如下。`
`- Euler …`
`- Heun …` | | Callout prefixes only: `💡` `⚠️` `✅` `❌` (others won't get class) | renderer maps these to `callout-info/warn/good/bad` | `> ⚠️ **FP16 overflow** — 即使除了 √d_k …` | | Math: `$...$` inline, `$$...$$` display, `$$\boxed{...}$$` for key boxes | MathJax CDN; literal in source | — | | Code: ```python fences, **real PyTorch that would run** | reviewer will check executability | — | | Personal-info banlist: `SJTU JHC`, `JHC PhD`, `Server5`, `job market`, `/Users/...`, specific lab/company names | reviewer flags as FAIL | byline goes via `--author` at render time, not in body | | Language: Chinese primary, English technical terms in-place | matches established cheat-sheet style | "softmax 饱和", "vector field" | ### Eyebrow / subt