Paper Accepted at EMNLP 2024

Pleased to share that our paper, Latent Concept-based Explanation of NLP Models, has been accepted at EMNLP 2024!

This paper continues our series of work on interpretability. We introduce a method called LACOAT (Latent Concept Attribution) that connects predictions with latent concepts present in a model’s representation. Hence, we move beyond attribution to individual tokens in the input to a more holistic concept.

The code is available on GitHub. Congratulations to Xuemin, Nadir, Marzia, and Hassan on this work!