Papers by Adrian Sauter
Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider (2026.acl-industry)
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| Challenge: | Managing customer churn is vital for subscription-based businesses . large language models (LLMs) can automate the classification of chursn-intent at scale . lack of transparency forces a difficult choice between automated systems and manual review . |
| Approach: | They propose to use text bottleneck models to classify customer churn in subscription-based businesses . they show that the model can be used to bridge the perceived trade-off between interpretability andpredictive performance . |
| Outcome: | The proposed model performs competitively with black-box baselines and an interactive dashboard. |