Short papers
4 pages, references excluded, double-blind reviewed
Machine Learning/CORE Unranked
AI-Native Academia @ NeurIPS 2026
NeurIPS 2026 Workshop on AI-Native Academia: Authorship, Peer Review, and Conference Governance under AI
The AI-Native Academia @ NeurIPS 2026 workshop explores how AI is transforming academic publishing—authorship, peer review, citation, and governance—and calls for redesigning scholarly institutions to address emerging failures like AI-generated reviews, citation hallucination, and human-AI co-hallucination. It brings together program chairs from top venues to develop shared taxonomies, security models, and governance frameworks for an AI-integrated academic pipeline.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Long papers
9 pages, references excluded, double-blind reviewed
Research areas in scope
01
AI-Native Academic Pipeline
AI-Assisted Authorship and Submission IntegrityAdversarial Manuscripts and Submission-Side AttacksAI-Assisted Peer Review and Reviewer AccountabilityMeta-Review, PCs, and Conference-Scale Decision SupportHuman-AI Co-Hallucination and Cross-Role Error PropagationCitation, Credit, and Scholarly Knowledge IntegrityProvenance, Plagiarism, Detection, and Due ProcessRecursive Scholarly Feedback Loops and Corpus ContaminationPublication Infrastructure, Policy, and Venue Repositioning
Policies worth checking twice
- Submissions are double-blind reviewed
- References are excluded from page limits
- Submissions are non-archival
- Non-archival, under-reviewed NeurIPS papers can be submitted and given full consideration
- Use of the official NeurIPS 2026 LaTeX template on Overleaf is required
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026