Papers with human interpretability
SenteCon: Leveraging Lexicons to Learn Human-Interpretable Language Representations (2023.findings-acl)
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| Challenge: | In many settings, it is important to understand a model’s decision-making process. |
| Approach: | They propose a method for introducing human interpretability in deep language representations by encoding a passage of text as a layer of interpretable categories. |
| Outcome: | The proposed method outperforms existing interpretable language representations on downstream tasks and on agreement with human characterizations of the text. |
Structuring Radiology Reports: Challenging LLMs with Lightweight Models (2025.emnlp-main)
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Johannes Moll, Louisa Fay, Asfandyar Azhar, Sophie Ostmeier, Sergios Gatidis, Tim C. Lueth, Curtis Langlotz, Jean-Benoit Delbrouck
| Challenge: | Radiology reports lack a standardized format, limiting both interpretability and machine learning applications. |
| Approach: | They propose to use lightweight encoder-decoder models for structuring radiology reports . they compare models with eight open-source LLMs with prompting and in-context learning . |
| Outcome: | The proposed models outperform eight open-source LLMs on a human-annotated test set. |