The Impact of Stochasticity on the Rashomon Effect in Machine Learning

arXiv:2609.32934 · cs.LG · Submitted 2026-09-26 · Read on arXiv

cs.LG

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Accuracy — 25× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Integrated Gradients — 6× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Interpretability — 4× in this paper · explained in 15 episodes
• Layer-wise Relevance Propagation — 4× in this paper
• Vanilla Gradients — 4× in this paper
• Accountability — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Layer-wise Relevance Propagation (LRP) — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Xplainable Artificial Intelligence — 1× in this paper

Sources

• Explanation sensitivity to the randomness of large language models: the case of journalistic text classification
• On the Rashomon ratio of infinite hypothesis sets
• The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
• Order in the Court: Explainable AI Methods Prone to Disagreement
• Can we Agree? On the Rash\=omon Effect and the Reliability of Post-Hoc Explainable AI
• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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