Ijcai Topic Selection

---
name: ijcai-topic-selection
description: Use when deciding whether an AI project is a strong IJCAI or IJCAI-ECAI fit, comparing main track versus special tracks, Survey Track, AIJ/JAIR expedited-publication potential, or alternative AI venues such as NeurIPS, ICML, ICLR, AAAI, AISTATS, UAI, COLT, KDD, CVPR, ACL, or ICRA.
---

# IJCAI Topic Selection

Use this before writing. IJCAI main-track submissions should report significant, original,
previously unpublished AI results with broad relevance to the AI community.

## Fit test

- Ask whether the paper advances an AI problem, AI technique, AI application domain, or
  cross-disciplinary AI boundary rather than only reporting an application result.
- Prefer IJCAI when the contribution is broadly AI-facing, technically complete in a compact
  format, and can survive a two-phase review process with limited response leverage.
- Consider special tracks for human-centered AI, AI for social good, AI4Tech, AI and health,
  or AI and robotics when the venue-specific framing is stronger than a general main-track
  frame.
- Consider the Survey Track only for mature areas and author teams with established topic
  expertise.
- Route elsewhere if the contribution is primarily ML theory, representation learning,
  computer vision, NLP, robotics, HCI, systems, or data mining and a specialist venue has a
  clearer audience.
- Check policy fit early: anonymity, recent rejection disclosures, dual-submission limits,
  data ethics, LLM-use constraints, and in-person presentation feasibility.

## Output format

```text
[Fit] strong IJCAI / possible IJCAI / better elsewhere
[Best track] main / special / survey / other venue
[Contribution sentence] <one sentence>
[Top rejection risk] <novelty/clarity/evidence/policy/scope>
[Next action] <experiment, framing, related work, or venue switch>
```