A curated escape route from AI research busywork

What it does This repository is essentially a categorized bookmark collection and mini-review blog compressed into a README. The author rounds up dozens of tools across the entire AI research lifecycle—paper discovery, reading, coding experiments, writing, and submission—adding brief personal notes about which ones they actually use versus which ones are still on their “to try” list.

The interesting bit Rather than dumping links, the author sorts them by workflow stage and adds blunt asides: Mendeley is what they currently use, Hyperopt is “to be tried,” and one PyTorch code repo is flagged because part of the implementation is hidden inside the authors’ own package. That honesty makes it more useful than a generic awesome-list.

Key highlights

• Covers the full research pipeline: RSS trend tracking, arXiv navigation, literature management, PyTorch templates, experiment logging, LaTeX helpers, and conference submission tools.
• Includes practical notes on Chinese-accessible workflows, such as using dblp to avoid needing a VPN and pairing Zotero with Jianguoyun for cross-device sync.
• Flags many entries as “待尝试” (not yet tried), so you know which recommendations are battle-tested and which are aspirational.
• Sections go deep on niche pain points: convolution-size visualizers, table-to-LaTeX converters, figure-drawing tools, and even white-noise generators for focus.

Caveats

• The entire document is in Chinese, so non-readers will need a translator.
• A number of entries are marked as untried by the author themselves, so the list mixes verified picks with speculative ones.
• It is purely a text directory; there are no screenshots or demo media to preview the tools.

Verdict Grab this if you are an AI researcher (especially a Chinese-speaking grad student) looking for a sanity-checked starting point rather than yet another exhaustive awesome-list. Skip it if you need code, automation, or English-language documentation.