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[1]
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Shammur Absar Chowdhury, Nadir Durrani, and Ahmed Ali.
What do end-to-end speech models learn about speaker, language and
channel information? a layer-wise and neuron-level analysis.
Computer Speech & Language, 83:101539, jan 2024.
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[2]
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Yimin Fan, Fahim Dalvi, Nadir Durrani, and Hassan Sajjad.
Evaluating neuron interpretation methods of NLP models.
In Thirty-seventh Conference on Neural Information Processing
Systems, December 2023.
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[3]
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Basel Mousi, Nadir Durrani, and Fahim Dalvi.
Can llms facilitate interpretation of pre-trained language models?
In Proceedings of the 2023 Conference on Empirical Methods in
Natural Language Processing. Association for Computational Linguistics,
December 2023.
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[4]
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Fahim Dalvi, Hassan Sajjad, and Nadir Durrani.
NeuroX library for neuron analysis of deep NLP models.
In Proceedings of the 61st Annual Meeting of the Association for
Computational Linguistics (Volume 3: System Demonstrations), pages 226--234,
Toronto, Canada, July 2023. Association for Computational Linguistics.
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[5]
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Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Tamim Jaban, Mus'ab Husaini, and
Ummar Abbas.
NxPlain: A web-based tool for discovery of latent concepts.
In Proceedings of the 17th Conference of the European Chapter of
the Association for Computational Linguistics: System Demonstrations, pages
75--83, Dubrovnik, Croatia, May 2023. Association for Computational
Linguistics.
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[6]
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Hassan Sajjad, Fahim Dalvi, Nadir Durrani, and Preslav Nakov.
On the effect of dropping layers of pre-trained transformer models.
Computer Speech and Language, 77(C):101429, jan 2023.
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[7]
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Firoj Alam, Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Abdul Rafae Khan, and
Jia Xu.
Conceptx: A framework for latent concept analysis.
Proceedings of the AAAI Conference on Artificial Intelligence,
37(13):16395--16397, Sep. 2023.
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[8]
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Ahmed Abdelali, Nadir Durrani, Fahim Dalvi, and Hassan Sajjad.
Post-hoc analysis of arabic transformer models.
In Proceedings of the Fifth BlackboxNLP Workshop on Analyzing
and Interpreting Neural Networks for NLP, Abu Dhabi, United Arab Emirates,
December 2022. Association for Computational Linguistics.
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[9]
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Nadir Durrani, Hassan Sajjad, Fahim Dalvi, and Firoj Alam.
On the transformation of latent space in fine-tuned NLP models.
In Proceedings of the 2022 Conference on Empirical Methods in
Natural Language Processing, pages 1495--1516, Abu Dhabi, United Arab
Emirates, December 2022. Association for Computational Linguistics.
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[10]
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Hassan Sajjad, Nadir Durrani, and Fahim Dalvi.
Neuron-level interpretation of deep NLP models: A survey.
Transactions of the Association for Computational Linguistics,
10:1285--1303, nov 2022.
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[11]
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Hassan Sajjad, Firoj Alam, Fahim Dalvi, and Nadir Durrani.
Effect of post-processing on contextualized word representations.
In Proceedings of the 29th International Conference on
Computational Linguistics, pages 3127--3142, Gyeongju, Republic of Korea,
October 2022. International Committee on Computational Linguistics.
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[12]
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Hassan Sajjad, Nadir Durrani, Fahim Dalvi, Firoj Alam, Abdul Khan, and Jia Xu.
Analyzing encoded concepts in transformer language models.
In Proceedings of the 2022 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language
Technologies, pages 3082--3101, Seattle, United States, July 2022.
Association for Computational Linguistics.
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[13]
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Fahim Dalvi, Abdul Khan, Firoj Alam, Nadir Durrani, Jia Xu, and Hassan Sajjad.
Discovering latent concepts learned in BERT.
In International Conference on Learning Representations, may
2022.
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[14]
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Nadir Durrani, Hassan Sajjad, and Fahim Dalvi.
How transfer learning impacts linguistic knowledge in deep NLP
models?
In Findings of the Association for Computational Linguistics:
ACL-IJCNLP 2021, pages 4947--4957, Online, August 2021. Association for
Computational Linguistics.
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[15]
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Hassan Sajjad, Narine Kokhlikyan, Fahim Dalvi, and Nadir Durrani.
Fine-grained interpretation and causation analysis in deep NLP
models.
In Proceedings of the 2021 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language
Technologies: Tutorials, pages 5--10, Online, June 2021. Association for
Computational Linguistics.
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[16]
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Fahim Dalvi, Hassan Sajjad, Nadir Durrani, and Yonatan Belinkov.
Analyzing redundancy in pretrained transformer models.
In Proceedings of the 2020 Conference on Empirical Methods in
Natural Language Processing (EMNLP), pages 4908--4926, Online, November
2020. Association for Computational Linguistics.
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[17]
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Nadir Durrani, Hassan Sajjad, Fahim Dalvi, and Yonatan Belinkov.
Analyzing individual neurons in pre-trained language models.
In Proceedings of the 2020 Conference on Empirical Methods in
Natural Language Processing (EMNLP), pages 4865--4880, Online, November
2020. Association for Computational Linguistics.
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[18]
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John Wu, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, and James
Glass.
Similarity analysis of contextual word representation models.
In Proceedings of the 58th Annual Meeting of the Association for
Computational Linguistics, pages 4638--4655, Online, July 2020. Association
for Computational Linguistics.
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[19]
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Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass.
On the linguistic representational power of neural machine
translation models.
Computational Linguistics, 46(1):1--52, March 2020.
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[20]
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Nadir Durrani, Fahim Dalvi, Hassan Sajjad, Yonatan Belinkov, and Preslav Nakov.
One size does not fit all: Comparing NMT representations of
different granularities.
In Proceedings of the 2019 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long and Short Papers), pages 1504--1516,
Minneapolis, Minnesota, June 2019. Association for Computational Linguistics.
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[21]
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Fahim Dalvi, Avery Nortonsmith, D. Anthony Bau, Yonatan Belinkov, Hassan
Sajjad, Nadir Durrani, and James Glass.
Neurox: A toolkit for analyzing individual neurons in neural
networks.
In AAAI Conference on Artificial Intelligence (AAAI), January
2019.
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[22]
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Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, D. Anthony Bau,
and James Glass.
What is one grain of sand in the desert? analyzing individual neurons
in deep nlp models.
In Proceedings of the Thirty-Third AAAI Conference on Artificial
Intelligence (AAAI, Oral presentation), January 2019.
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[23]
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Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, and
James Glass.
Identifying and controlling important neurons in neural machine
translation.
In International Conference on Learning Representations, 2019.
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[24]
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Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, and Stephan Vogel.
Understanding and improving morphological learning in the neural
machine translation decoder.
In Proceedings of the Eighth International Joint Conference on
Natural Language Processing (Volume 1: Long Papers), pages 142--151, Taipei,
Taiwan, November 2017. Asian Federation of Natural Language Processing.
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[25]
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Yonatan Belinkov, Lluís Màrquez, Hassan Sajjad, Nadir Durrani, Fahim
Dalvi, and James Glass.
Evaluating layers of representation in neural machine translation on
part-of-speech and semantic tagging tasks.
In Proceedings of the Eighth International Joint Conference on
Natural Language Processing (Volume 1: Long Papers), pages 1--10, Taipei,
Taiwan, November 2017. Asian Federation of Natural Language Processing.
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[26]
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Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass.
What do Neural Machine Translation Models Learn about Morphology?
In Proceedings of the 55th Annual Meeting of the Association for
Computational Linguistics (ACL), Vancouver, July 2017. Association for
Computational Linguistics.
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