Tag: interpretability
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Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Model
Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Model arXiv:2504.21795v1 Announce Type: new Abstract: The Hawkes process (HP) is commonly used to model event sequences with self-reinforcing dynamics, including electronic health records (EHRs). Traditional HPs capture self-reinforcement via parametric impact functions that can be inspected to understand how each…
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Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests
Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests arXiv:2504.18498v1 Announce Type: new Abstract: Functional survival models are key tools for analyzing time-to-event data with complex predictors, such as functional or high-dimensional inputs. Despite their predictive strength, these models often lack interpretability, which limits their value in practical decision-making and risk analysis. This…
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Towards Interpretable Soft Prompts
Towards Interpretable Soft Prompts arXiv:2504.02144v1 Announce Type: cross Abstract: Soft prompts have been popularized as a cheap and easy way to improve task-specific LLM performance beyond few-shot prompts. Despite their origin as an automated prompting method, however, soft prompts and other trainable prompts remain a black-box method with no immediately interpretable connections to prompting. We…