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05/26/2023
NeuroX Library for Neuron Analysis of Deep NLP Models
Neuron analysis provides insights into how knowledge is structured in re...
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03/06/2023
NxPlain: Web-based Tool for Discovery of Latent Concepts
The proliferation of deep neural networks in various domains has seen an...
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01/30/2023
Evaluating Neuron Interpretation Methods of NLP Models
Neuron Interpretation has gained traction in the field of interpretabili...
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11/12/2022
ConceptX: A Framework for Latent Concept Analysis
The opacity of deep neural networks remains a challenge in deploying sol...
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11/10/2022
Impact of Adversarial Training on Robustness and Generalizability of Language Models
Adversarial training is widely acknowledged as the most effective defens...
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10/23/2022
On the Transformation of Latent Space in Fine-Tuned NLP Models
We study the evolution of latent space in fine-tuned NLP models. Differe...
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10/18/2022
Post-hoc analysis of Arabic transformer models
Arabic is a Semitic language which is widely spoken with many dialects. ...
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06/27/2022
Analyzing Encoded Concepts in Transformer Language Models
We propose a novel framework ConceptX, to analyze how latent concepts ar...
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06/27/2022
Linguistic Correlation Analysis: Discovering Salient Neurons in deepNLP models
While a lot of work has been done in understanding representations learn...
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05/15/2022
Discovering Latent Concepts Learned in BERT
A large number of studies that analyze deep neural network models and th...
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04/13/2022
Probing for Constituency Structure in Neural Language Models
In this paper, we investigate to which extent contextual neural language...
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01/19/2022
Interpreting Arabic Transformer Models
Arabic is a Semitic language which is widely spoken with many dialects. ...
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08/30/2021
Neuron-level Interpretation of Deep NLP Models: A Survey
The proliferation of deep neural networks in various domains has seen an...
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05/31/2021
How transfer learning impacts linguistic knowledge in deep NLP models?
Transfer learning from pre-trained neural language models towards downst...
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05/17/2021
Fine-grained Interpretation and Causation Analysis in Deep NLP Models
This paper is a write-up for the tutorial on "Fine-grained Interpretatio...
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04/15/2021
Effect of Post-processing on Contextualized Word Representations
Post-processing of static embedding has beenshown to improve their perfo...
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10/06/2020
Analyzing Individual Neurons in Pre-trained Language Models
While a lot of analysis has been carried to demonstrate linguistic knowl...
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07/15/2020
Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms
With the outbreak of the COVID-19 pandemic, people turned to social medi...
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05/03/2020
Similarity Analysis of Contextual Word Representation Models
This paper investigates contextual word representation models from the l...
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04/30/2020
Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society
Disinformation, i.e., information that is both false and means harm, thr...
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04/14/2020
Standardizing and Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing
Time-critical analysis of social media streams is important for humanita...
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04/08/2020
Exploiting Redundancy in Pre-trained Language Models for Efficient Transfer Learning
Large pre-trained contextual word representations have transformed the f...
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04/08/2020
Poor Man's BERT: Smaller and Faster Transformer Models
The ongoing neural revolution in Natural Language Processing has recentl...
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03/31/2020
A Clustering Framework for Lexical Normalization of Roman Urdu
Roman Urdu is an informal form of the Urdu language written in Roman scr...
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02/27/2020
Compressing Large-Scale Transformer-Based Models: A Case Study on BERT
Transformer-based models pre-trained on large-scale corpora achieve stat...
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11/01/2019
On the Linguistic Representational Power of Neural Machine Translation Models
Despite the recent success of deep neural networks in natural language p...
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06/27/2019
Findings of the First Shared Task on Machine Translation Robustness
We share the findings of the first shared task on improving robustness o...
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12/21/2018
NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks
We present a toolkit to facilitate the interpretation and understanding ...
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12/21/2018
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models
Despite the remarkable evolution of deep neural networks in natural lang...
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11/03/2018
Identifying and Controlling Important Neurons in Neural Machine Translation
Neural machine translation (NMT) models learn representations containing...
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06/10/2018
Incremental Decoding and Training Methods for Simultaneous Translation in Neural Machine Translation
We address the problem of simultaneous translation by modifying the Neur...
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01/23/2018
Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks
While neural machine translation (NMT) models provide improved translati...
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09/02/2017
Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging
Word segmentation plays a pivotal role in improving any Arabic NLP appli...
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08/29/2017
Neural Machine Translation Training in a Multi-Domain Scenario
In this paper, we explore alternative ways to train a neural machine tra...
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04/11/2017
What do Neural Machine Translation Models Learn about Morphology?
Neural machine translation (MT) models obtain state-of-the-art performan...
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01/14/2017
QCRI Machine Translation Systems for IWSLT 16
This paper describes QCRI's machine translation systems for the IWSLT 20...
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10/04/2016
Applications of Online Deep Learning for Crisis Response Using Social Media Information
During natural or man-made disasters, humanitarian response organization...
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08/12/2016
Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networks
The role of social media, in particular microblogging platforms such as ...
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06/18/2016
