ServiceNow AI Research

Interpretability

Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale …
Shubham Gupta, Zichao Li, Tianyi Chen, Cem Subakan, Siva Reddy, Perouz Taslakian, Valentina Zantedeschi
International Conference on Machine Learning (ICML),  2026.
Article Citation Code Vidéo
Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale …
Shubham Gupta, Zichao Li, Tianyi Chen, Cem Subakan, Siva Reddy, Perouz Taslakian, Valentina Zantedeschi
Workshop at the International Conference of Machine Learning (ICML),  2026.
Article Citation Vidéo
Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. …
Agathe Balayn, Lorenzo Corti, Fanny Rancourt, Fabio Casati, Ujwal Gadiraju
Conference on Human Factors in Computing Systems (ACM-CHI),  2024.
Article Citation Vidéo
Invariant Causal Set Covering Machines
Invariant Causal Set Covering Machines
Rule-based models, such as decision trees, appeal to practitioners due to their interpretable nature. However, the learning algorithms …
Thibaud Godon, Baptiste Bauvin, Pascal Germain, Jacques Corbeil, Alexandre Drouin
Workshop on Spurious Correlations, Invariance, and Stability (ICML),  2023.
Article Citation Code
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data

Recent metabolomics measurement devices, such as mass spectrometers, produce extremely high-dimensional data. Together with small …

Thibaud Godon, Pier-Luc Plante, Baptiste Bauvin, Élina Francovic-Fontaine, Alexandre Drouin, François Laviolette, Jacques Corbeil
Intelligent Systems for Molecular Biology and European Conference on Computational Biology,  2021.
Article Citation Code Vidéo
Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability
Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability
To date, there has been no formal study of the statistical cost of interpretability in machine learning. As such, the discourse around …
Gintare Karolina Dziugaite, Shai Ben-David, Daniel M. Roy
ArXiv,  2020.
Article Citation
Interpretable genotype-to-phenotype classifiers with performance guarantees
Interpretable genotype-to-phenotype classifiers with performance guarantees
Understanding the relationship between the genome of a cell and its phenotype is a central problem in precision medicine. Nonetheless, …
Alexandre Drouin, Gaël Letarte, Frédéric Raymond, Mario Marchand, Jacques Corbeil, François Laviolette
Nature Scientific Reports,  2018.
Article Citation Code