ARIS-in-AI-Offer (ARIS in 秋招)

Hoping to make your 秋招 (qiūzhāo, Chinese AI campus recruiting season) a little easier 🌱

📖 中文版 (Chinese version): README_CN.md

📚 Jump to a topic — 23 first-party cheat sheets across 7 categories + 1 community-contributed category:

🧠 General / Foundations · 🎯 Post-Training & Reasoning · 🏛️ LLM Architecture & Systems · 🌊 Generative Models — Theory & Tokenizers · 🎨 Generation Systems (Image / Video / 3D / Diffusion Post-Training) · 👁️ Multimodal · 🤖 Agents · 🦾 Embodied AI / 具身智能

Or browse the full 📚 Tutorial Index ↓ · jump to 🌐 ARIS-Homepage ↓.

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🏆 Built on a battle-tested foundation — the ARIS main repo has ~10k GitHub stars, was HuggingFace Daily Papers #1, won AI Digital Crew Project of the Day, and ships 74+ research skills across 7+ platforms. This isn't a vaporware preview — every cheat sheet here is the production output of the same /interview-cheatsheet + /render-html workflow used in academic-research production.

A curated, bilingual (中文 + English) collection of ML / LLM / multimodal / diffusion / agent / generative-model interview cheat sheets, auto-generated by the ARIS — Auto Research in Sleep /render-html workflow.

Each cheat sheet is a long-form Chinese tutorial with: formula derivations · from-scratch PyTorch code · 25 high-frequency interview questions (L1 essentials · L2 advanced · L3 top-tier lab).

🔥 NEW · 🌐 Also in this repo — ARIS-Homepage: turn your CV + selected GitHub repos into a fact-checked academic homepage with single-file HTML output. v1.1 adds --from-repos owner/repo,... — gh CLI snapshots stars / releases / READMEs and merges repo timelines into your homepage. 🔥 Live demo at wanshuiyin.github.io →

📖 Preview (above): one snapshot per pillar, taken from the Diffusion Foundations cheat sheet — ① Foundations (formula derivations + intuition + TL;DR), ② Interview Q&A (25 high-frequency questions stratified L1/L2/L3), ③ From-Scratch Code (runnable PyTorch, including CFG training + DDIM sampling). Every cheat sheet in this collection follows the same three-pillar structure.

🌐 ARIS-Homepage preview (above): same /render-html workflow turning a CV into a fact-checked academic homepage. Live demo at wanshuiyin.github.io. Details + pipeline diagram in the ARIS-Homepage section ↓.

📝 Long-form blog preview (above): a standalone hand-authored long-form technical survey. A Survey on Continuous DLM (2026 H1, 6 papers) — Chinese-language survey by Ruofeng Yang (SJTU), written end-to-end via cross-model discussion (Claude Opus 4.7 + Codex GPT-5.5 xhigh + Gemini auto-gemini-3). 📖 Read full blog ↗.

📱 HTML reads cleanly everywhere

Phone on the subway, iPad at a café, laptop in the library — same HTML link opens equally well:

• 🧮 MathJax renders all LaTeX formulas (not screenshots — scalable, copyable, selectable)
• 💻 highlight.js colors all PyTorch code blocks
• 📐 Responsive layout adapts to any window width — no overflow, no blur
• 📑 Sticky TOC for jumping around long documents
• 💾 Single-file HTML — download once, read offline, no backend required

📢 What's New

• 2026-06-08 — 🔧 tools/render_html.py now strips a leading UTF-8 BOM before frontmatter detection (6cc4876).
• 2026-06-05 — 🔭 Community Showcase: an online tutorial-collection site by @QiZishi — merges all 23 Chinese tutorials here with Datawhale Hello-Agents' LLM interview Q&A into one card-index reading site (read online · from #3). The README gains a Community Showcase section listing community derivatives — build something on top of these tutorials and open an issue to get it listed (f8e7d33).
• 2026-06-02 — 📝 Two new blogs — Continuous DLM (representation perspective, v2) + Diffusion × Representation × Manifold — the Continuous DLM survey is upgraded to a representation-perspective expansion (replacing the earlier v1), and a companion blog traces the "borrow representation / use the manifold" threads across image & video diffusion (SSL / Consistency / REPA / RAE / JiT / V-JEPA2). Both hand-authored, cross-model reviewed; the two cross-reference each other. Live: continuous_dlm_representation_perspective.html · diffusion_representation_manifold.html. See the Blog Index ↓.
• 2026-06-01 — 📝 New blog: a deep-dive guide to NVIDIA Cosmos 3 (omnimodal world model · MoT architecture) — a long-form Chinese popsci walkthrough of the 138-page Cosmos 3 technical report (15 sections · 12 figures): how understanding and generation are stitched into one Transformer (Mixture-of-Transformers), the training recipe, scaling / serving, and the three model sizes. Reviewed end-to-end across 5 rounds of Codex GPT-5.5 xhigh cross-model audit (numbers + mechanisms checked, overclaims trimmed). Self-contained single-file HTML at docs/blogs/cosmos3_mot_guide.html — a hand-authored guide (ELF blog format), not part of the audited /render-html pipeline. All figures and numbers are from the NVIDIA Cosmos 3 report (github.com/nvidia/cosmos); © the original authors, used here as an attributed popsci guide.
• 2026-05-31 — 🔍 Cross-model audit pass — real errors caught & fixed across the whole collection, now CI-enforced — a fresh Codex GPT-5.5 xhigh re-review of every cheat sheet (中文 + EN) surfaced genuine technical mistakes the first pass had missed, and fixed them: DeepSeek-V3's FP8 GEMM accumulates in FP32, not bf16; Qwen2-VL M-RoPE base is 1e6; Molmo's vision tower is CLIP, not SigLIP; TensoRF complexity is O(N³); a broken StreamingLLM render callout; plus 10 EN translation-fidelity fixes (meaning reversals, a dropped framework list). Every docs/ artifact now carries a traceable cross-model review, and a new CI gate (tools/verify_reviews.py --mode strict --reproduce, wired in review-audit.yml) blocks any PR whose HTML isn't a reviewed view that byte-reproduces from its source — so no un-reviewed or hand-edited content can land. Also merged today: a Focus-dim reading mode for --blog-mode pages (dim non-current sections · floating 🎯 toggle · ↑/↓ section nav), reflowed from the dllm blog effort into the academic templa