# OAIXiv

Open AI Xiv (OAIXiv) is an AI-driven academic preprint platform. After researchers upload a paper, the system automatically calls multiple large AI models (currently Mimo and Deepseek) for independent review, aggregates via voting, and within 3-5 minutes produces a structured quality-assessment report across six dimensions. In one line: upload paper → multi-model AI consult → see scores and concrete improvement suggestions on novelty, methodology, reproducibility, writing quality, literature coverage, and research importance. Core features 1. Multi-model AI review (core): not a single AI score. Three or more independent models each review the same dimension, take the median, and mark confidence. Larger model disagreement means lower confidence—you know at a glance whether the review is reliable. 2. Six-dimension structured report: not a vague blurb. Novelty, methodological rigor, reproducibility, writing quality, literature coverage, research importance—each scored independently (1-10) with concrete comments, strengths, gaps, and revision suggestions (high/medium/low priority). 3. Version evolution tracking: revise a version, re-review once. 4. Native multilingual review: AI can review Chinese papers directly—no English translation first. Bilingual Chinese–English UI and cross-language paper discovery. Use cases — Scene one: pre-submission "pre-checkup" when a first draft is done but quality is uncertain.

Open AI Xiv (OAIXiv) is an AI-driven academic preprint platform. After researchers upload a paper, the system automatically calls multiple large AI models (currently Mimo and Deepseek) for independent review, aggregates via voting, and within 3-5 minutes produces a structured quality-assessment report across six dimensions. In one line: upload paper → multi-model AI consult → see scores and concrete improvement suggestions on novelty, methodology, reproducibility, writing quality, literature coverage, and research importance. Core features 1. Multi-model AI review (core): not a single AI score. Three or more independent models each review the same dimension, take the median, and mark confidence. Larger model disagreement means lower confidence—you know at a glance whether the review is reliable. 2. Six-dimension structured report: not a vague blurb. Novelty, methodological rigor, reproducibility, writing quality, literature coverage, research importance—each scored independently (1-10) with concrete comments, strengths, gaps, and revision suggestions (high/medium/low priority). 3. Version evolution tracking: revise a version, re-review once. 4. Native multilingual review: AI can review Chinese papers directly—no English translation first. Bilingual Chinese–English UI and cross-language paper discovery. Use cases — Scene one: pre-submission "pre-checkup" when a first draft is done but quality is uncertain.

Canonical: https://uniquebase.ai/products/oaixiv
Stable identifier: UB-D7179
Snapshot captured: 2026-10-29T00:45:28.937Z
English updated: 2026-10-29T00:52:59.441Z

## Connected profiles

- [OAIXiv](/companies/oaixiv)

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