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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 21 1 Interpreting Arabic Transformer Models ... Abdelali, Ahmed; Durrani, Nadir; Dalvi, Fahim. - : arXiv, 2022 BASE Show details 2 How transfer learning impacts linguistic knowledge in deep NLP models? ... Durrani, Nadir; Sajjad, Hassan; Dalvi, Fahim. - : arXiv, 2021 Abstract: 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 learn non-trivial amount of linguistic knowledge, captured at different layers of the model. We investigate how fine-tuning towards downstream NLP tasks impacts the learned linguistic knowledge. We carry out a study across popular pre-trained models BERT, RoBERTa and XLNet using layer and neuron-level diagnostic classifiers. We found that for some GLUE tasks, the network relies on the core linguistic information and preserve it deeper in the network, while for others it forgets. Linguistic information is distributed in the pre-trained language models but becomes localized to the lower layers post fine-tuning, reserving higher layers for the task specific knowledge. The pattern varies across architectures, with BERT retaining linguistic information relatively deeper in the network compared to RoBERTa and XLNet, where it is ... : Findings of the ACL 2021 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2105.15179 https://dx.doi.org/10.48550/arxiv.2105.15179 BASE Hide details 3 How transfer learning impacts linguistic knowledge in deep NLP models? ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Dalvi, Fahim; Durrani, Nadir. - : Underline Science Inc., 2021 BASE Show details 4 Effect of Post-processing on Contextualized Word Representations ... Sajjad, Hassan; Alam, Firoj; Dalvi, Fahim. - : arXiv, 2021 BASE Show details 5 Similarity Analysis of Contextual Word Representation Models ... Wu, John M.; Belinkov, Yonatan; Sajjad, Hassan. - : arXiv, 2020 BASE Show details 6 AraBench: Benchmarking Dialectal Arabic-English Machine Translation ... The 28th International Conference on Computational Linguistics 2020; Abdelali, Ahmed; Dalvi, Fahim. - : Underline Science Inc., 2020 BASE Show details 7 A Clustering Framework for Lexical Normalization of Roman Urdu ... Khan, Abdul Rafae; Karim, Asim; Sajjad, Hassan. - : arXiv, 2020 BASE Show details 8 Analyzing Individual Neurons in Pre-trained Language Models ... Durrani, Nadir; Sajjad, Hassan; Dalvi, Fahim. - : arXiv, 2020 BASE Show details 9 On the Linguistic Representational Power of Neural Machine Translation Models Belinkov, Yonatan; Durrani, Nadir; Dalvi, Fahim... In: Computational Linguistics, Vol 46, Iss 1, Pp 1-52 (2020) (2020) BASE Show details 10 On the Linguistic Representational Power of Neural Machine Translation Models ... Belinkov, Yonatan; Durrani, Nadir; Dalvi, Fahim. - : arXiv, 2019 BASE Show details 11 What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models ... Dalvi, Fahim; Durrani, Nadir; Sajjad, Hassan. - : arXiv, 2018 BASE Show details 12 Identifying and Controlling Important Neurons in Neural Machine Translation ... Bau, Anthony; Belinkov, Yonatan; Sajjad, Hassan. - : arXiv, 2018 BASE Show details 13 The Summa Platform Prototype ... Liepins, Renars; Germann, Ulrich; Barzdins, Guntis. - : Zenodo, 2017 BASE Show details 14 The Summa Platform Prototype ... Liepins, Renars; Germann, Ulrich; Barzdins, Guntis. - : Zenodo, 2017 BASE Show details 15 Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging ... Sajjad, Hassan; Dalvi, Fahim; Durrani, Nadir. - : arXiv, 2017 BASE Show details 16 The SUMMA Platform Prototype Riedel, Sebastian; Garner, Phil; Narayan, Shashi... In: http://infoscience.epfl.ch/record/233575 (2017) BASE Show details 17 Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015 ... Sajjad, Hassan; Durrani, Nadir; Guzman, Francisco. - : arXiv, 2016 BASE Show details 18 QCMUQ@QALB-2015 Shared Task: Combining Character level MT and Error-tolerant Finite-State Recognition for Arabic Spelling Correction ... Bouamor, Houda; Sajjad, Hassan; Durrani, Nadir. - : Carnegie Mellon University, 2015 BASE Show details 19 QCMUQ@QALB-2015 Shared Task: Combining Character level MT and Error-tolerant Finite-State Recognition for Arabic Spelling Correction ... Bouamor, Houda; Sajjad, Hassan; Durrani, Nadir. - : Carnegie Mellon University, 2015 BASE Show details 20 Hindi-to-Urdu machine translation through transliteration Durrani, Nadir; Sajjad, Hassan; Fraser, Alexander... In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 48 (2010) 1, 465-474 BLLDB Show details Page: 1 2

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