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BAKER: Bayesian Kernel Uncertainty in Domain-Specific Document Modelling
Azam, Ubaid Razzak, Imran Vishwakarma, Shelly Hacid, Hakim Zhang, Dell Jameel, Shoaib
Azam, Ubaid
Razzak, Imran
Vishwakarma, Shelly
Hacid, Hakim
Zhang, Dell
Jameel, Shoaib
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3701551.3703517.pdf
Adobe PDF, 1.11 MB
Supervisor
Department
Computational Biology
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
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Abstract
In critical domains such as healthcare and law, accurately modelling the uncertainty of automatic computational models is essential. For instance, healthcare models must produce reliable estimates to guide human decision-making. However, modelling uncertainty remains challenging, particularly for models handling low-resource datasets and complex, domain-specific vocabulary. Most existing predictive models model point estimates rather than probability distributions, limiting our ability to quantify model uncertainty. This paper introduces a novel model, BAKER, designed to address these limitations. BAKER combines the strengths of Bayesian inference, known for its effectiveness in modelling uncertainty, and kernel methods, which excel at capturing complex data relationships. Incorporating kernel functions enhances model performance, particularly by reducing overfitting in data-limited scenarios. Our experimental analysis shows that BAKER significantly improves uncertainty reasoning compared to existing models.
Citation
Y. Tanaka et al., “Beyond Click to Cognition: Effective Interventions for Promoting Examination of False Beliefs in Misinformation,” Conference on Human Factors in Computing Systems - Proceedings , vol. 18, Apr. 2025, doi: https://doi.org/10.1145/3701551.3703517
Source
Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining
Conference
WSDM '25: The Eighteenth ACM International Conference on Web Search and Data Mining Hannover Germany March 10 - 14, 2025
Keywords
Language models, Bayesian Inference, Kernel methods, Reliability
Subjects
Source
WSDM '25: The Eighteenth ACM International Conference on Web Search and Data Mining Hannover Germany March 10 - 14, 2025
Publisher
Association for Computing Machinery