mli/paper-reading resource
深度学习经典、新论文逐段精读 observed · 2026-08-28
Health v2 · maintenance only
38/100
- Activity 12
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1776
- days_rel: n/a
- days_push: 529
- n_releases_24m: 0
Adoption not part of the score
33735 stars · 2806 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A curated collection of in-depth video walkthroughs of classic and recent deep learning papers, presented paragraph by paragraph by Mu Li. The repository indexes recorded lectures (on Bilibili and YouTube) covering papers like Sora, Llama 3.1, and GPT-4.
Use cases
- learn deep learning by reading classic papers
- understand the Llama 3.1 paper in detail
- find guided explanations of GPT-4 and Sora papers
- get a reading list of important ML papers
- watch paper walkthroughs with expert commentary
When to choose
- you want expert, paragraph-by-paragraph explanations of landmark deep learning papers
- you prefer video lectures over reading papers alone
- you want a curated, continuously updated paper reading list
When to avoid
- you need runnable code or a software tool rather than educational content
- you need English-only content since lectures are in Chinese
- you want interactive tutorials or exercises
Facets
learning-resource · maturity active
deep-learning documentation deep-learning large-language-models tutorials paper-reading video-lectures reading-list bilibili chinese-content web-server
1 source
- readme: https://github.com/mli/paper-reading · fetched 2026-08-28 · 00b6e454a3d4
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| mli/paper-reading | main | 38 |
For agents
markdown · JSON · MCP: product_card(name="mli/paper-reading")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem