Nadir Durrani

Latest

• Evaluating Neuron Interpretation Methods of NLP Models
• NxPlain: A Web-based Tool for Discovery of Latent Concepts
• Discovering Salient Neurons in deep NLP models
• On the Transformation of Latent Space in Fine-Tuned NLP Models
• Post-hoc analysis of Arabic transformer models
• Effect of Post-processing on Contextualized Word Representations
• Analyzing Encoded Concepts in Transformer Language Models
• Discovering Latent Concepts Learned in BERT
• Neuron-level Interpretation of Deep NLP Models: A Survey
• On the Effect of Dropping Layers of Pre-trained Transformer Models
• How transfer learning impacts linguistic knowledge in deep NLP models?
• Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms
• Fine-grained Interpretationand Causation Analysis in Deep NLP Models
• AraBench: Benchmarking Dialectal Arabic-English Machine Translation
• Analyzing Individual Neurons in Pre-trained Language Models
• Analyzing Redundancy in Pretrained Transformer Models
• Similarity Analysis of Contextual Word Representation Models
• On the Linguistic Representational Power of Neural Machine Translation Models
• One Size Does Not Fit All: Comparing NMT Representations of Different Granularities
• Identifying and Controlling Important Neurons in Neural Machine Translation
• What is one Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models
• NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks
• Incremental Decoding and Training Methods for Simultaneous Translation in Neural Machine Translation
• Neural Machine Translation Training in a Multi-Domain Scenario
• Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks
• Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder
• Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging
• What do Neural Machine Translation Models Learn about Morphology?
• QCRI Live Speech Translation System
• Domain Adaptation using Neural Network Joint Model
• A Deep Fusion Model for Domain Adaptation in Phrase-based MT
• QCRI’s Machine Translation Systems for IWSLT’2016
• Eyes Don't Lie: Predicting Machine Translation Quality Using Eye Movement.
• Using Joint Models for Domain Adaptation in Statistical Machine Translation
• How to Avoid Unwanted Pregnancies: Domain Adaptation using Neural Network Models
• QCMUQ@QALB-2015 Shared Task: Combining Character level MT and Error-tolerant Finite-State Recognition for ArabicSpelling Correction
• QCN Egyptian Arabic to English MachineTranslation System for NIST OpenMT15
• Integrating an Unsupervised Transliteration Model into Statistical Machine Translation
• Munich-Edinburgh-Stuttgart Submissions at WMT13: Morphological and Syntactic Processing for SMT
• Munich-Edinburgh-Stuttgart Submissions of OSM Systems at WMT13
• QCRI-MES Submission at WMT13: Using Transliteration Mining to Improve Statistical Machine Translation
• Comparing Two Techniques for Learning Transliteration Models Using a Parallel Corpus
• Hindi-to-Urdu Machine Translation through Transliteration