Fetching the paper…
Reading the bibliography…
While a lot of work has been done in understanding representations learned within deep NLP models and what knowledge they capture, little attention has been paid towards individual neurons.
Discovery of natural language concepts in individual units of cnns
Seil Na, Yo Joong Choe, Dong-Hyun Lee, and Gunhee Kim · 1902
Earlier work this paper cites.
Are sixteen heads really better than one?
Paul Michel, Omer Levy, and Graham Neubig · 1905
Earlier work this paper cites.
Unsupervised transfer learning via BERT neuron selection
Mehrdad Valipour, En-Shiun Annie Lee, Jaime R. Jamacaro, and Carolina Bessega · 1912
Earlier work this paper cites.
Introduction to the CoNLL-2000 shared task chunking
Erik F. Tjong Kim Sang and Sabine Buchholz · 2000
Earlier work this paper cites.
SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia · 2001
Earlier work this paper cites.
Empirical methods for compound splitting
Philipp Koehn and Kevin Knight · 2003
Earlier work this paper cites.
Building a large annotated corpus of English: The Penn Treebank
Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz · 2004
Earlier work this paper cites.
Automatically constructing a corpus of sentential paraphrases
William B. Dolan and Chris Brockett · 2005
Earlier work this paper cites.
Rdrpostagger: A ripple down rules-based part-of-speech tagger
Dat Quoc Nguyen, Dai Quoc Nguyen, Dang Duc Pham, and Son Bao Pham · 2005
Earlier work this paper cites.
Finding experts in transformer models
Xavier Suau, Luca Zappella, and Nicholas Apostoloff · 2005
Earlier work this paper cites.
Regularization and variable selection via the elastic net
Hui Zou and Trevor Hastie · 2005
Earlier work this paper cites.
Creating a CCGbank and a wide-coverage CCG lexicon for German
Julia Hockenmaier · 2006
Earlier work this paper cites.
Compositional explanations of neurons
Jesse Mu and Jacob Andreas · 2006
Earlier work this paper cites.
Computing optimal subsets
Maxim Binshtok, Ronen I Brafman, Solomon Eyal Shimony, Ajay Martin, and Crag Boutilier · 2007
Earlier work this paper cites.
The fifth pascal recognizing textual entailment challenge
Luisa Bentivogli, Ido Dagan, Hoa Trang Dang, Danilo Giampiccolo, and Bernardo Magnini · 2009
Earlier work this paper cites.
A universal part-of-speech tagset
Slav Petrov, Dipanjan Das, and Ryan McDonald · 2012
Earlier work this paper cites.
Knowledge sources for constituent parsing of German, a morphologically rich and less-configurational language
Alexander Fraser, Helmut Schmid, Richárd Farkas, Renjing Wang, and Hinrich Schütze · 2013
Earlier work this paper cites.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
T. Hastie, R. Tibshirani, and J. Friedman · 2013
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, Radu Soricut, Lucia Specia, and Aleš Tamchyna · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps, 2014
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
Earlier work this paper cites.
Visualizing and understanding recurrent networks, 2015
Andrej Karpathy, Justin Johnson, and Li Fei-Fei · 2015
Earlier work this paper cites.
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg · 2016
Earlier work this paper cites.
Visualizing and understanding neural models in NLP
Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky · 2016
Earlier work this paper cites.
Analyzing Linguistic Knowledge in Sequential Model of Sentence
Peng Qian, Xipeng Qiu, and Xuanjing Huang · 2016
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
Earlier work this paper cites.
Does string-based neural MT learn source syntax?
Xing Shi, Inkit Padhi, and Kevin Knight · 2016
Earlier work this paper cites.
Word Representation Models for Morphologically Rich Languages in Neural Machine Translation
Ekaterina Vylomova, Trevor Cohn, Xuanli He, and Gholamreza Haffari · 2016
Cited alongside, same era.
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
Cited alongside, same era.
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder
Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, and Stephan Vogel · 2017
Cited alongside, same era.
Dieuwke Hupkes, Sara Veldhoen, and Willem H. Zuidema · 2017
Cited alongside, same era.
Representation of linguistic form and function in recurrent neural networks
On the linguistic representational power of neural machine translation models
Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass · 2020
Later among the works it cites.
German’s next language model
Branden Chan, Stefan Schweter, and Timo Möller · 2020
Later among the works it cites.
Unsupervised cross-lingual representation learning at scale, 2020
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov · 2020
Later among the works it cites.
Analyzing redundancy in pretrained transformer models
Fahim Dalvi, Hassan Sajjad, Nadir Durrani, and Yonatan Belinkov · 2020
Later among the works it cites.
The shapley taylor interaction index, 2020
Kedar Dhamdhere, Ashish Agarwal, and Mukund Sundararajan · 2020
Later among the works it cites.
Explaining explanations: Axiomatic feature interactions for deep networks, 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ákos Kádár, Grzegorz Chrupała, and Afra Alishahi · 2017
Cited alongside, same era.
A unified approach to interpreting model predictions
Scott M Lundberg and Su-In Lee · 2017
Cited alongside, same era.
Axiomatic attribution for deep networks, 2017
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
Cited alongside, same era.
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
Cited alongside, same era.
How important is a neuron?, 2018
Kedar Dhamdhere, Mukund Sundararajan, and Qiqi Yan · 2018
Cited alongside, same era.
Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave, Tal Linzen, and Marco Baroni · 2018
Cited alongside, same era.
Mode: Automated neural network model debugging via state differential analysis and input selection
Shiqing Ma, Yingqi Liu, Wen Chuan Lee, Xiangyu Zhang, and Ananth Grama · 2018
Cited alongside, same era.
Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen · 2018
Cited alongside, same era.
Joseph D. Janizek, Pascal Sturmfels, and Su-In Lee · 2020
Later among the works it cites.
Are pre-trained language models aware of phrases? simple but strong baselines for grammar induction, 2020
Taeuk Kim, Jihun Choi, Daniel Edmiston, and Sang goo Lee · 2020
Later among the works it cites.
FlauBERT: Unsupervised language model pre-training for French
Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoit Crabbé, Laurent Besacier, and Didier Schwab · 2020
Later among the works it cites.
FIND: Human-in-the-Loop Debugging Deep Text Classifiers
Piyawat Lertvittayakumjorn, Lucia Specia, and Francesca Toni · 2020
Later among the works it cites.
UMAP: Uniform manifold approximation and projection for dimension reduction, 2020
Leland Mclnnes, John Healy, and James Melville · 2020
Later among the works it cites.
Richard Meyes, Constantin Waubert de Puiseau, Andres Posada-Moreno, and Tobias Meisen · 2020
Later among the works it cites.
When BERT Plays the Lottery, All Tickets Are Winning
Sai Prasanna, Anna Rogers, and Anna Rumshisky · 2020
Later among the works it cites.
Tx-ray: Quantifying and explaining model-knowledge transfer in (un-)supervised NLP
Nils Rethmeier, Vageesh Kumar Saxena, and Isabelle Augenstein · 2020
Later among the works it cites.
Intrinsic probing through dimension selection
Lucas Torroba Hennigen, Adina Williams, and Ryan Cotterell · 2020
Later among the works it cites.
How does this interaction affect me? interpretable attribution for feature interactions, 2020
Michael Tsang, Sirisha Rambhatla, and Yan Liu · 2020
Later among the works it cites.
Amnesic probing: Behavioral explanation with amnesic counterfactuals
Yanai Elazar, Shauli Ravfogel, Alon Jacovi, and Yoav Goldberg · 2021
Later among the works it cites.
CausaLM: Causal model explanation through counterfactual language models
Amir Feder, Nadav Oved, Uri Shalit, and Roi Reichart · 2021
Later among the works it cites.
Improving explainability and accuracy through feature engineering: A taxonomy of features in nlp-based machine learning
Thiemo Wambsganss, Christiane Engel, and Hansjörg Fromm · 2021
Later among the works it cites.
On the pitfalls of analyzing individual neurons in language models
Omer Antverg and Yonatan Belinkov · 2022
Closest in time.
On the transformation of latent space in fine-tuned nlp models
Nadir Durrani, Hassan Sajjad, Fahim Dalvi, and Firoj Alam · 2022
Closest in time.
Analyzing encoded concepts in transformer language models
Hassan Sajjad, Nadir Durrani, Fahim Dalvi, Firoj Alam, Abdul Khan, and Jia Xu · 2022
Closest in time.
On the effect of dropping layers of pre-trained transformer models
Hassan Sajjad, Fahim Dalvi, Nadir Durrani, and Preslav Nakov · 2022
Closest in time.
What do end-to-end speech models learn about speaker, language and channel information? a layer-wise and neuron-level analysis
Shammur Absar Chowdhury, Nadir Durrani, and Ahmed Ali · 2023
Closest in time.
Neurox library for neuron analysis of deep nlp models
Fahim Dalvi, Nadir Durrani, and Hassan Sajjad · 2023
Closest in time.
Can llms facilitate interpretation of pre-trained language models?
Basel Mousi, Nadir Durrani, and Fahim Dalvi · 2023
Closest in time.
Feature learning in deep classifiers through intermediate neural collapse
Marius Rangamani, Akshay; Lindegaard, Tomer Galanti, and Tomaso Poggio · 2023
Closest in time.
A latent-variable model for intrinsic probing, 2023
Karolina Stańczak, Lucas Torroba Hennigen, Adina Williams, Ryan Cotterell, and Isabelle Augenstein · 2023
Closest in time.