281 citations · 652 across the 50 of their papers we have counts for
8 papers · 1 filter
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…
Analyzing Encoded Concepts in Transformer Language Models
Hassan Sajjad, Nadir Durrani, Fahim Dalvi +3
We propose a novel framework ConceptX, to analyze how latent concepts are encoded in representations learned within pre-trained language models. It uses clustering to discover the…
Discovering Salient Neurons in Deep NLP Models
Nadir Durrani, Fahim Dalvi, Hassan Sajjad
While a lot of work has been done in understanding representations learned within deep NLP models and what knowledge they capture, little attention has been paid towards individual…
NatiQ: An End-to-end Text-to-Speech System for Arabic
Ahmed Abdelali, Nadir Durrani, Cenk Demiroglu +3
NatiQ is end-to-end text-to-speech system for Arabic. Our speech synthesizer uses an encoder-decoder architecture with attention. We used both tacotron-based models (tacotron-1 and…
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…
Interpreting 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…