ChicagoHAI/OpenAIReview

OpenAIReview — AI-Powered Academic Paper Reviewer

we recommend using uv, and there are additional guidelines for best results with PDF inputs

How do authors want to use AI for review?

A survey of researchers who compared AI-generated scientific reviews with journal-agnostic human peer review reveals that they overwhelmingly prefer using AI as a self-checking tool before submission rather than as a replacement for human reviewers. It encourages an “author-centric” model in which AI helps researchers improve their manuscripts before they are reviewed by their peers.

AI-powered Literature Review & Synthesis

Recording from my workshop last week on smarter literature review with AI

AI Research Assistant Claude Scholar: Open Source, Free, and Citation-Verified | João Cláudio Nunes Carvalho posted on the topic | LinkedIn

🚨 Professors are going to hate this. Someone just open sourced an AI that writes research papers from idea to publication. Conference-ready. Citation-verified. Free. It's called Claude Scholar. An AI-powered research system that handles every step of the academic workflow. Idea to publication. Fully automated. No advisor at 2am. No staring at blank LaTeX files. No crying during rebuttal season. Here's what's inside this thing: → AI brainstorms research topics, reviews literature, and finds gaps nobody has explored → Runs statistical analysis on your experiments. t-tests, ANOVA, ablation studies. Publication-ready figures. → Writes your paper section by section. Abstract to conclusion. Conference-formatted. → Verifies every citation through multi-layer validation so AI never hallucinates a reference → Strips robotic AI language and adds human voice so reviewers can't tell → Self-reviews your draft with a 6-point quality checklist before you submit → Parses reviewer comments, classifies each one, and drafts your entire rebuttal Here's the wildest part: It supports NeurIPS, ICML, ICLR, ACL, AAAI, Nature, Science, Cell, and PNAS. Downloads the conference template, strips sample content, and gives you a clean LaTeX structure ready to write into. The creator says it covers 90% of the academic research lifecycle. Research assistants charge $30 to $60/hour. Conference paper consultants charge $5,000+. Graduate programs cost $50K/year. This is free. All of it. 100% Open Source.

Adil on Twitter / X

being assigned to review AI generated slop papers is very frustrating. the way this is supposed to work is that first you take the time to write something and then i take the time to read it. if you don't do the first part then i shouldn't have to do the second part.— Adil (@adilsoubki) August 26, 2026

AI-assisted Reviewing is Necessary and Should be Open

Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.

AI-assisted Reviewing is Necessary and Should be Open

Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.

AI reviewers are here — we are not ready

Nature - Artificial intelligence promises rapid and polite feedback on papers — but we must first review the reviewer.

Peer review is overwhelmed—can it survive in the AI era?

As research and AI-assisted papers surge, volunteer reviewers struggle to keep up.

Google opens Deep Review AI tool to help researchers catch manuscript errors

Google Research on Oct. 14 released Deep Review, an AI system designed to flag mathematical errors, logical gaps and unsupported claims in technical documents. The public launch follows pilots that provided feedback on more than 15,000 manuscripts, according to Google. Speaking at Google’s Research@ event in Mountain View, California, Rajesh Jayaram, a research scientist at…

AI-Assisted Tools in the CHI 2027 Papers Review Process: What They Do, What They Do Not Do, and How Humans Remain Responsible - ACM CHI 2027

AI-Assisted Tools in the CHI 2027 Papers Review Process: What They Do, What They Do Not Do, and How Humans Remain Responsible Authors: Anna Cox, Tony Tang, Thomas Kosch, Erin Solovey, Petra Isenberg, Regan MandrykDate: 2026-08-29 Introduction In our recent post explaining the CHI 2027 Papers review process, we said we would pilot several AI-assisted […]

Socialize the Plan

On AI and code review.

OpenAccess.ai — Rigorous Open Access Publishing

$20 to submit, free to read. AI peer review. Open to human and machine authors. All articles CC-BY 4.0.

AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot

Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances in AI have led the community to consider its use in peer review, yet a key unresolved question is whether AI can generate technically sound reviews at real-world conference scale. Here we report the first large-scale field deployment of AI-assisted peer review: every main-track submission at AAAI-26 received one clearly identified AI review from a state-of-the-art system. The system combined frontier models, tool use, and safeguards in a multi-stage process to generate reviews for all 22,977 full-review papers in less than a day. A large-scale survey of AAAI-26 authors and program committee members showed that participants not only found AI reviews useful, but actually preferred them to human reviews on key dimensions such as technical accuracy and research suggestions. We also introduce a novel benchmark and find that our system substantially outperforms a simple LLM-generated review baseline at detecting a variety of scientific weaknesses. Together, these results show that state-of-the-art AI methods can already make meaningful contributions to scientific peer review at conference scale, opening a path toward the next generation of synergistic human-AI teaming for evaluating research.

AI peer review goes pro

A what we're reading spotlight