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We propose a novel framework ConceptX, to analyze how latent concepts are encoded in representations learned within pre-trained language models.
RoBERTa: A robustly optimized BERT pretraining approach
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Finding experts in transformer models
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Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2016 · 2016
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Visualizing and understanding neural models in NLP
Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky. 2016 · 2016
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Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg. 2016 · 2016
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Investigating Language Universal and Specific Properties in Word Embeddings
Peng Qian, Xipeng Qiu, and Xuanjing Huang. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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The parallel meaning bank: Towards a multilingual corpus of translations annotated with compositional meaning representations
Lasha Abzianidze, Johannes Bjerva, Kilian Evang, Hessel Haagsma, Rik van Noord, Pierre Ludmann, Duc-Duy Nguyen, and Johan Bos. 2017 · 2017
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Representation of linguistic form and function in recurrent neural networks
Akos Kádár, Grzegorz Chrupała, and Afra Alishahi. 2017 · 2017
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Linguistic knowledge and transferability of contextual representations
Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith. 2019a · 2019
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Visualizing and measuring the geometry of BERT
Emily Reif, Ann Yuan, Martin Wattenberg, Fernanda B Viegas, Andy Coenen, Adam Pearce, and Been Kim. 2019 · 2019
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BERT rediscovers the classical NLP pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
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A multiscale visualization of attention in the transformer model
Jesse Vig. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
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On the linguistic representational power of neural machine translation models
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Word representation models for morphologically rich languages in neural machine translation
Ekaterina Vylomova, Trevor Cohn, Xuanli He, and Gholamreza Haffari. 2017 · 2017
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Deep RNNs encode soft hierarchical syntax
Terra Blevins, Omer Levy, and Luke Zettlemoyer. 2018 · 2018
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What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Alexis Conneau, German Kruszewski, Guillaume Lample, Loïc Barrault, and Marco Baroni. 2018 · 2018
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Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave, Tal Linzen, and Marco Baroni. 2018 · 2018
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Dieuwke Hupkes, Sara Veldhoen, and Willem Zuidema. 2018 · 2018
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Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav)
Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, et al. 2018 · 2018
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Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen. 2018 · 2018
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Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass. 2020 · 2020
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Concept whitening for interpretable image recognition
Zhi Chen, Yijie Bei, and Cynthia Rudin. 2020 · 2020
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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Analyzing individual neurons in pre-trained language models
Nadir Durrani, Hassan Sajjad, Fahim Dalvi, and Yonatan Belinkov. 2020 · 2020
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Emergence of separable manifolds in deep language representations
Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, and Sueyeon Chung. 2020 · 2020
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Asking without telling: Exploring latent ontologies in contextual representations
Julian Michael, Jan A. Botha, and Ian Tenney. 2020 · 2020
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A primer in BERTology: What we know about how BERT works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2020 · 2020
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Similarity analysis of contextual word representation models
John Wu, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, and James Glass. 2020 · 2020
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Probing classifiers: Promises, shortcomings, and alternatives
Yonatan Belinkov. 2021 · 2021
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How transfer learning impacts linguistic knowledge in deep NLP models?
Nadir Durrani, Hassan Sajjad, and Fahim Dalvi. 2021 · 2021
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Fine-grained interpretation and causation analysis in deep NLP models
Hassan Sajjad, Narine Kokhlikyan, Fahim Dalvi, and Nadir Durrani. 2021 · 2021
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Discovering latent concepts learned in BERT
Fahim Dalvi, Abdul Rafae Khan, Firoj Alam, Nadir Durrani, Jia Xu, and Hassan Sajjad. 2022 · 2022
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