# AAAI 2026 review form > Simulate AAAI-style reviews: Summary, Strengths and Weaknesses, Questions for the Authors, four criterion ratings, and the 1–8 Overall Evaluation, written in AAAI's depersonalized voice. - Venue: AAAI Conference on Artificial Intelligence - Form status: modeled, not official. The AAAI review form is not public. The field list follows a published description of the AAAI-25 form; the four criterion labels (Excellent/Good/Fair/Poor) and the 1–8 overall labels are modeled on AAAI/IJCAI conventions, not official wording. - Official source: https://aaai.org/conference/aaai/aaai-26/instructions-for-aaai-26-reviewers/ - Overall score: Overall Evaluation, 1–8 - Rough acceptance bar (our simulation): mean ≥ 5 - Web page: https://reviewpaper.ai/venues/aaai ## How reviewers read the paper AAAI reviewers assess the paper's story (problem, limits of the state of the art, whether results support the claims, key novelty), presentation (soundness, clarity, unstated assumptions, reproducibility, limitations), related work, and evaluations (baselines, metrics, datasets, error analysis), separating essential from optional revisions. Reviews must be depersonalized and must not duplicate content from other reviews, including AAAI's own AI review. Review is two-phase: papers with clearly negative Phase-1 ratings are rejected before author feedback. - Depersonalize: avoid "I", "you" and "the authors"; write "the paper" or "this reviewer". - Professional and respectful. - Separate essential revisions from optional suggestions. **Where the bar sits.** AAAI-26 accepted 17.6% of 23,680 submissions, and Phase 1 removes many papers before author feedback. No public score statistics; rough rule: mean ≥ 5 (of 8) needed to be competitive. ## Reviewer form, field by field ### 1. Summary Type: free text. The main claims and contributions of the paper. ### 2. Strengths Type: list of points. Part of "Strengths And Weaknesses". Cover the story (problem, limits of the state of the art, key novel contribution), presentation, placement in related work, and evaluation. ### 3. Weaknesses Type: list of points. Part of "Strengths And Weaknesses". Do the results support the claims? Unstated assumptions, missing reproducibility detail, missing related work, weak baselines/metrics/datasets/error analysis. Separate essential revisions from optional ones. ### 4. Questions For The Authors Type: list of points. Questions whose answers could change the evaluation. These feed the single author-feedback window. ### 5. Significance Of The Problem Type: score, 1–4. Excellent / Good / Fair / Poor. - **4**: excellent - **3**: good - **2**: fair - **1**: poor ### 6. Justification Of Approach Type: score, 1–4. Excellent / Good / Fair / Poor. - **4**: excellent - **3**: good - **2**: fair - **1**: poor ### 7. Quality Of Evaluation Type: score, 1–4. Excellent / Good / Fair / Poor. - **4**: excellent - **3**: good - **2**: fair - **1**: poor ### 8. Reproducibility And Facilitation Of Follow Up Work Type: score, 1–4. Excellent / Good / Fair / Poor. - **4**: excellent - **3**: good - **2**: fair - **1**: poor ### 9. Ethical Considerations Type: free text. Responsible research practice: human subjects, sensitive data, bias. "None" if not applicable. ### 10. Overall Evaluation Type: score, 1–8. Overall recommendation on AAAI's eight-point scale. - **8**: Strong accept (top 5% of accepted papers) - **7**: Accept (top 15% of accepted papers) - **6**: Weak accept - **5**: Borderline accept - **4**: Borderline reject - **3**: Weak reject - **2**: Reject - **1**: Strong reject ### 11. Confidence Type: score, 1–5. How certain you are about your assessment. - **5**: You are absolutely certain about your assessment. You are very familiar with the related work and checked the math/other details carefully. - **4**: You are confident in your assessment, but not absolutely certain. It is unlikely, but not impossible, that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. - **3**: You are fairly confident in your assessment. It is possible that you did not understand some parts of the submission or that you are unfamiliar with some pieces of related work. Math/other details were not carefully checked. - **2**: You are willing to defend your assessment, but it is quite likely that you did not understand the central parts of the submission or that you are unfamiliar with some pieces of related work. Math/other details were not carefully checked. - **1**: Your assessment is an educated guess. The submission is not in your area or the submission was difficult to understand. Math/other details were not carefully checked. ## Area chair meta-review AAAI SPCs write the meta-review and the AC confirms the decision. Recommendation options: Accept · Reject ## AAAI Reproducibility Checklist 1. General: motivation, contributions and pedagogical references clearly stated 2. Theory: all assumptions stated and complete proofs provided 3. Datasets: new datasets described and released (or reasons given); licensing of existing datasets 4. Code: source code for experiments released or will be released 5. Experiments: random seeds, hardware, hyperparameters and their selection reported 6. Experiments: evaluation metrics motivated; statistical significance / variance reported 7. Page limit: 7 pages of content plus up to 2 pages of references ## LLM policy No explicit AAAI reviewer-LLM rule was found, but reviewer confidentiality rules in practice forbid uploading submissions to external LLMs. AAAI supplies its own official AI review, and reviewers must not duplicate content from other reviews. Official policy: https://aaai.org/conference/aaai/aaai-26/ethical-guidelines-for-aaai-26-reviewers/ --- Simulate reviews of your own draft in this venue's form: https://reviewpaper.ai/new?venue=aaai (3 free reviews). Sample report: https://reviewpaper.ai/sample. reviewpaper.ai is for authors checking their own unpublished drafts. If you are an assigned reviewer, follow your venue's LLM policy: most venues forbid putting a submission you are reviewing into any external AI tool. Not affiliated with any conference.