--- name: AAAI Related Work slug: aaai-related-work category: Writing description: Assists authors in writing related work sections for AAAI papers that clearly differentiate novelty, handle contemporaneous non-archival work within policy constraints, and address reviewer pushback patterns. github: "https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAAI-Skills/skills/aaai-related-work" language: Stata stars: 875 forks: 106 install: "git clone https://github.com/brycewang-stanford/Awesome-Journal-Skills" added: 2026-07-20T06:49:35.920Z last_synced: 2026-07-28T07:01:23.641Z canonical_url: "https://dirskills.com/skills/aaai-related-work" --- # AAAI Related Work Assists authors in writing related work sections for AAAI papers that clearly differentiate novelty, handle contemporaneous non-archival work within policy constraints, and address reviewer pushback patterns. **Install:** `git clone https://github.com/brycewang-stanford/Awesome-Journal-Skills` ## README # AAAI Related Work Use this to make the novelty claim robust under AAAI's broad AI review. The related-work section must help reviewers distinguish the paper from both archival work and contemporaneous non-archival work. ## Positioning checks - Identify the closest archival AI papers and current arXiv/workshop work. - Separate method novelty, task novelty, evaluation novelty, and system integration novelty. - Cite contemporaneous non-archival work carefully when it affects priority or reviewer expectations. - Do not submit substantially similar work to multiple archival venues at the same time. - Explain how the paper differs from AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors in assumptions, evidence, scope, and contribution. - Avoid using AI systems as citable scientific sources under AAAI policy. ## Novelty paragraph Use this structure: ```text Closest prior work solves under . It does not address . This paper contributes and verifies it through . The claim is limited to . ``` ## Positioning across AAAI's breadth AAAI spans search, planning, knowledge representation, constraint satisfaction, multi-agent systems, learning, NLP, vision, and robotics, so the closest prior work may live in a subfield your reviewer does not. Make the contrast explicit for a non-specialist instead of assuming shared background. | Neighbor venue | Reviewer expectation | Differentiation to spell out | | --- | --- | --- | | IJCAI | broad-AI overlap | what your result adds beyond their framing | | NeurIPS/ICML | ML method or theory depth | why AAAI breadth, not just a benchmark gain | | ICLR | representation-learning lens | non-learning mechanism or guarantee you contribute | | AAAI prior years | incremental-track suspicion | the new assumption, evidence, or scope | ## Reviewer-pushback patterns - "This looks concurrent with arXiv paper Y." Fix: cite Y, state it is non-archival and contemporaneous, and name the specific setting or evidence you add; do not bury or ignore it. - "Isn't this the same as your workshop paper?" Fix: clarify the archival delta and confirm no substantially similar work is under review elsewhere, satisfying the dual-submission rule. - "Citation looks AI-generated." Fix: verify every reference against a real source; AAAI policy bars AI systems as citable scientific sources and hallucinated citations are a credibility risk. ## Worked vignette A reasoning-over-knowledge-graphs paper sits near both a KR archival line and a recent NeurIPS embedding paper. Using the axes: against KR work the difference is *evidence* (learned vs. hand-built rules); against the NeurIPS neighbor it is *scope* (logical soundness, not just link prediction). One contemporaneous arXiv preprint is cited as non-archival with a one-line delta, and the dual-submission box is checked clean. ## Output format ```text [Closest work] [Difference axis] problem / method / theory / data / evaluation / system / impact [Must-cite items] [Multiple-submission risk] none / clarify / withdraw / reroute [Revision text] ```