whatisgithub

What is icml2026-guide-cn?

jenniferzhao0531/icml2026-guide-cn — explained in plain English

Analysis updated 2026-05-18

21HTMLAudience · researcherComplexity · 2/5LicenseSetup · easy

In one sentence

A bilingual browsing guide with Chinese summaries for all 6,567 papers accepted at the ICML 2026 machine learning conference.

Mindmap

mindmap
  root((ICML2026 Guide CN))
    What it does
      Organizes 6567 papers
      Adds Chinese summaries
      Highlights Spotlight papers
    Tech stack
      Python
      HTML
      OpenAI-compatible LLMs
    Use cases
      Browse ICML papers
      Search by title or author
      Filter Spotlight papers
    Audience
      Chinese speaking researchers

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Browse all ICML 2026 accepted papers organized into a three-level Chinese-language hierarchy.

USE CASE 2

Search papers by title or author directly in a single static webpage.

USE CASE 3

Filter down to the 575 highest-rated Spotlight papers with one click.

USE CASE 4

Run your own pipeline to crawl, classify, and summarize a different conference's papers.

What is it built with?

PythonHTMLOpenAI-compatible API

How does it compare?

jenniferzhao0531/icml2026-guide-cnhurapanda/cheespiguo45/single-file-wbs
Stars212121
LanguageHTMLHTMLHTML
Setup difficultyeasyeasyeasy
Complexity2/52/51/5
Audienceresearchergeneralpm founder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

The published webpage needs no setup, running the pipeline yourself requires an OpenAI-compatible API key.

Free to use, modify, and redistribute for any purpose, including commercial use, as long as you keep the copyright notice.

So what is it?

ICML 2026 Guide CN is a Chinese-language browsing guide for all 6,567 accepted papers from the ICML 2026 machine learning conference. ICML (the International Conference on Machine Learning) is one of the most influential academic venues for AI research. This project makes it easier to explore that large collection by organizing every paper into a three-level hierarchy and adding a six-dimensional Chinese summary to each one. The tool works in two modes. The first is a ready-made static webpage, a single HTML file with no external dependencies, already published online. It has a three-level collapsible navigation on the left, a full-text search box for titles and authors, and a one-click filter to show only the 575 Spotlight papers (the conference's highest-rated submissions, highlighted with a gold badge). The second mode lets you run the pipeline yourself: four Python scripts crawl the official ICML data, call any OpenAI-compatible language model to classify papers into subcategories and generate Chinese summaries across six dimensions (research motivation, problem being solved, observations, methods, data and experiments, and main contribution), and finally render everything into the HTML file. All LLM calls use an OpenAI-compatible interface, so you can point it at DeepSeek, Claude, or any compatible proxy with your own API key. You would use this if you are a Chinese-speaking researcher or student who wants to scan what was accepted at ICML 2026 without reading 6,567 English abstracts. The project is built with Python for the pipeline and plain HTML for the viewer, with MIT license.

Copy-paste prompts

Prompt 1
Open the ICML2026-Guide-CN static webpage and help me find Spotlight papers about a specific topic.
Prompt 2
Run the ICML2026-Guide-CN Python pipeline against my own conference paper list using an OpenAI-compatible API.
Prompt 3
Explain the six-dimensional Chinese summary format this project generates for each paper.
Prompt 4
Help me adapt ICML2026-Guide-CN's crawler and summarizer for a different academic conference.

Frequently asked questions

What is icml2026-guide-cn?

A bilingual browsing guide with Chinese summaries for all 6,567 papers accepted at the ICML 2026 machine learning conference.

What language is icml2026-guide-cn written in?

Mainly HTML. The stack also includes Python, HTML, OpenAI-compatible API.

What license does icml2026-guide-cn use?

Free to use, modify, and redistribute for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is icml2026-guide-cn to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is icml2026-guide-cn for?

Mainly researcher.

Open on GitHub → Ask about another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.