82 citations · 114 across the 11 of their papers we have counts for
20 papers
ConceptX: A Framework for Latent Concept Analysis
Firoj Alam, Fahim Dalvi, Nadir Durrani +3
The opacity of deep neural networks remains a challenge in deploying solutions where explanation is as important as precision. We present ConceptX, a human-in-the-loop framework fo…
On the Transformation of Latent Space in Fine-Tuned NLP Models
Nadir Durrani, Hassan Sajjad, Fahim Dalvi +1
We study the evolution of latent space in fine-tuned NLP models. Different from the commonly used probing-framework, we opt for an unsupervised method to analyze representations. M…
Post-hoc analysis of Arabic transformer models
Ahmed Abdelali, Nadir Durrani, Fahim Dalvi +1
Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects…
Discovering Latent Concepts Learned in BERT
Fahim Dalvi, Abdul Rafae Khan, Firoj Alam +3
A large number of studies that analyze deep neural network models and their ability to encode various linguistic and non-linguistic concepts provide an interpretation of the inner…
How transfer learning impacts linguistic knowledge in deep NLP models?
Nadir Durrani, Hassan Sajjad, Fahim Dalvi
Transfer learning from pre-trained neural language models towards downstream tasks has been a predominant theme in NLP recently. Several researchers have shown that deep NLP models…
Fine-grained Interpretation and Causation Analysis in Deep NLP Models
Hassan Sajjad, Narine Kokhlikyan, Fahim Dalvi +1
This paper is a write-up for the tutorial on "Fine-grained Interpretation and Causation Analysis in Deep NLP Models" that we are presenting at NAACL 2021. We present and discuss th…