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Found 6 papers, 1 papers with code
Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies
As artificial neural networks grow in complexity, understanding their inner workings becomes increasingly challenging, which is particularly important in healthcare applications.
On the Sequence Evaluation based on Stochastic Processes
Recent methods that utilize stochastic processes to capture the intrinsic dynamics of sequences have shown superior performance in generative modeling.
BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence
In summary, we present a novel Brownian bridge coherence metric capable of measuring both local and global text coherence, while circumventing the need for end-to-end model training.
Enhancing Robustness of Foundation Model Representations under Provenance-related Distribution Shifts
We focus on confounding by provenance, a form of distribution shift that emerges in the context of multi-institutional datasets when there are differences in source-specific language use and class distributions.
Backdoor Adjustment of Confounding by Provenance for Robust Text Classification of Multi-institutional Clinical Notes
Machine learning and deep learning approaches have been used to improve the performance of clinical NLP.
A Dialogue System for Assessing Activities of Daily Living: Improving Consistency with Grounded Knowledge
A lack of functioning may lead to poor living conditions requiring personal care and assistance.
