activity
20172025
most citedQCRI Machine Translation Systems for IWSLT 16

20 citations · 35 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2025

Beyond the Leaderboard: Understanding Performance Disparities in Large Language Models via Model Diffing

Sabri Boughorbel, Fahim Dalvi, Nadir Durrani +1

As fine-tuning becomes the dominant paradigm for improving large language models (LLMs), understanding what changes during this process is increasingly important. Traditional bench…

cs.CL2025

From Words to Waves: Analyzing Concept Formation in Speech and Text-Based Foundation Models

Asım Ersoy, Basel Mousi, Shammur Chowdhury +3

The emergence of large language models (LLMs) has demonstrated that systems trained solely on text can acquire extensive world knowledge, develop reasoning capabilities, and intern…

cs.CL2023

NeuroX Library for Neuron Analysis of Deep NLP Models

Fahim Dalvi, Hassan Sajjad, Nadir Durrani

Neuron analysis provides insights into how knowledge is structured in representations and discovers the role of neurons in the network. In addition to developing an understanding o…

cs.CL2023

NxPlain: Web-based Tool for Discovery of Latent Concepts

Fahim Dalvi, Nadir Durrani, Hassan Sajjad +3

The proliferation of deep neural networks in various domains has seen an increased need for the interpretability of these models, especially in scenarios where fairness and trust a…

cs.CL2022

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…

cs.CL201720 cited

QCRI Machine Translation Systems for IWSLT 16

Nadir Durrani, Fahim Dalvi, Hassan Sajjad +1

This paper describes QCRI's machine translation systems for the IWSLT 2016 evaluation campaign. We participated in the Arabic->English and English->Arabic tracks. We built both Phr…