IJCAI-ECAI 2026: Decision Notification and ChairingTool Status Thread [D]

2026-04-29 · Source: Machine Learning · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

The IJCAI-ECAI 2026 conference is experiencing delays in releasing final paper decision notifications, originally scheduled for April 29, 2026 AoE. This delay is attributed to the ChairingTool rollout and the volunteer nature of Program Committee (PC) members, who often face challenges like missing reviews. Historical data from recent IJCAI conferences suggests main-track acceptance rates of approximately 14% in 2023 and 2024, and 17-19% in 2025. For IJCAI-ECAI 2026, the estimated final acceptance rate is projected to be around 15-18%, with Phase 2 papers potentially seeing a higher acceptance probability of 22-28%. While some tracks, like Robotics and Survey, have begun releasing decisions, many main track submissions remain in "submitted" status, leading to author frustration regarding punctuality and transparency.

Key takeaway

For research scientists awaiting IJCAI-ECAI 2026 decisions, understand that delays are common in large conferences due to volunteer PC work and technical rollouts. While some tracks have released results, main track notifications may still be pending. Exercise patience and monitor the ChairingTool for status changes, as decisions are not released simultaneously across all submissions or tracks. Do not infer rejection solely from delayed notification.

Key insights

Conference paper notification delays are common due to volunteer PC work and platform rollouts, impacting author expectations.

Principles

• PC members are unpaid volunteers.
• Delays often stem from missing reviews.

In practice

• Check specific track notifications.
• Monitor ChairingTool status changes.

Topics

• IJCAI-ECAI 2026
• Conference Decisions
• Acceptance Rates
• ChairingTool
• Peer Review Process

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning.