Zhejiang University open-sources Polaris: AI pipeline for full research workflow
机器之心 · wechat · 2026-08-15
Zhejiang University team open-sourced Polaris, an AI platform that automates the entire research workflow, from literature review to paper writing. It chains six stages: literature survey, idea generation, idea review, experimentation, paper writing, and paper review, with human oversight at key decision points.
Key features:
- Literature survey: Daily arXiv scraping, AI-generated summaries and Chinese guides, deep dives, concept linking, semantic search, Obsidian export.
- Idea generation & review: Mines signals like concept gaps and paper limitations, AI reviewers debate in pairs and Elo-rank ideas; researchers decide which to advance.
- Experiment execution: Connects to GPU servers, AI designs experiments, writes code, trains, analyzes results, iterates; can pause to ask user questions; plan grows with evidence.
- Paper writing & review: Online LaTeX workbench, AI drafts sections, enforces that every number comes from real experiment logs and citations are real; AI peer review verifies each.
- Skill system: Customizable standards for review, experiment norms, etc.; built-in skills like literature review drafting and rebuttal writing.
- Collaboration: Shared literature library for labs, transparent usage metrics.
- Open integration: Exposes capabilities via MCP and skills for tools like Claude Code and Codex; desktop clients for macOS, Windows, Linux.
Open-sourced on GitHub, actively developed.
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