What is this?
The MindRL Hub Modeling Challenge is a cognitive modeling competition designed to redefine how we evaluate AI-era models. We move beyond simple predictive accuracy to a tripartite framework: Prediction + Explanation + Robustness (Attack).
Our Core Philosophy
- Prediction ≠ Explanation: High accuracy doesn’t guarantee a correct mechanism.
- Testability: Explanations must be falsifiable and scientifically rigorous.
- Robustness: A truly “good” model should remain valid under adversarial challenge.
The Tracks
We utilize a dual-track system where modeling and auditing are interactive rather than independent processes.
| Track | Focus | Goal |
|---|---|---|
| Generative Track | Modeling & Prediction | Build a predictive model and provide a verifiable “Interpretation Card.” |
| Adversarial Track | Auditing & Challenge | Systematically audit model claims, looking for edge cases and simpler alternative explanations. |
The Process
The challenge follows a rigorous, phase-based workflow to ensure high-quality, iterative research.
- Phase 1: Modeling – Baseline and initial model implementation.
- Phase 2: Interpretation – Submission of the Interpretation Card.
- Phase 3: Adversarial Challenge – Audit groups begin testing the models.
- Phase 4: Rebuttal & Correction – Models are refined based on challenges.
- Phase 5: Final Presentation – Complete demonstration of model, attack, and response.
Timeline (2026)
- May 17: Official Announcement & Launch
- May 29: Enrollment Opens
- June 15: Enrollment Deadline
- June 29: Phase 1 Starts (Task & Dataset Release)
- July 27: Phase 2 Starts (Adversarial Track)
- September 4: Presentation Day & Awards
Why Join?
We are not looking for a simple leaderboard. Our goal is to contribute to a standard for cognitive modeling in the AI era. You will gain:
- Deep experience in sequential decision-making and online adaptation.
- Exposure to systematic model auditing and failure-mode analysis.
- The chance to contribute to a perspective paper on the future of cognitive modeling standards.
Participation Note: Teams consist of 2-3 members with complementary skills in modeling and analysis.