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NeurIPS 2026 Workshop

XAI4Science

Knowledge Discovery and Trust through Interpretable Foundation Models
Dec 11/12, 2026
Sydney, Australia
Co-located with NeurIPS 2026

Weather and climate foundation models now rival physics-based forecasts at a fraction of the computational cost. But unlike models built on known equations, their reasoning is opaque, and they can quietly hallucinate. XAI4Science brings together ML researchers, climate scientists, and policy experts to make these models explainable, trustworthy, and physically grounded.

What the Workshop Covers
01

Ante-hoc
Interpretability

Self-explainable architectures and inductive biases for Foundation Models.

02

Post-hoc Attribution & Evaluation

Attribution and probing methods, evaluated for their faithfulness.

03

Physics-Consistent Explanations

Benchmarks that check explanations against known physical laws.

This is not an exhaustive list and applications to other Science domains are welcome. For any question reach out to xai4science@gmail.com.
Submission Deadline (23:59 AoE)
September 5, 2026
Submit via OpenReview →
Submissions are non-archival
Regular and Tiny tracks (with ≤8 and ≤5 pages respectively)
Organizers
Leonardo Pesce · Jiawen Wei · Gianmarco Mengaldo
National University of Singapore