Fetching the paper…
Reading the bibliography…
Probing classifiers have emerged as one of the prominent methodologies for interpreting and analyzing deep neural network models of natural language processing.
Do attention heads in bert track syntactic dependencies?
Htut, Phu Mon, Jason Phang, Shikha Bordia, and Samuel R Bowman. 2019 · 1911
Earlier work this paper cites.
On the shortest arborescence of a directed graph
CHU, Y. 1965 · 1965
Earlier work this paper cites.
Optimum branchings
Edmonds, Jack. 1967 · 1967
Earlier work this paper cites.
Representational similarity analysis - connecting the branches of systems neuroscience
Kriegeskorte, Nikolaus, Marieke Mur, and Peter Bandettini. 2008 · 2008
Earlier work this paper cites.
Distributional vectors encode referential attributes
Gupta, Abhijeet, Gemma Boleda, Marco Baroni, and Sebastian Padó. 2015 · 2015
Earlier work this paper cites.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Adi, Yossi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2016 · 2016
Earlier work this paper cites.
Understanding intermediate layers using linear classifier probes
Alain, Guillaume and Yoshua Bengio. 2016 · 2016
Earlier work this paper cites.
Probing for semantic evidence of composition by means of simple classification tasks
Ettinger, Allyson, Ahmed Elgohary, and Philip Resnik. 2016 · 2016
Earlier work this paper cites.
Does string-based neural MT learn source syntax?
Shi, Xing, Inkit Padhi, and Kevin Knight. 2016 · 2016
Earlier work this paper cites.
Diagnostic classifiers revealing how neural networks process hierarchical structure
Veldhoen, Sara, Dieuwke Hupkes, and Willem H Zuidema. 2016 · 2016
Earlier work this paper cites.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Adi, Yossi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2017 · 2017
Earlier work this paper cites.
Analyzing hidden representations in end-to-end automatic speech recognition systems
Belinkov, Yonatan and James Glass. 2017 · 2017
Earlier work this paper cites.
Investigating ‘aspect’ in NMT and SMT: Translating the english simple past and present perfect
Vanmassenhove, Eva, Jinhua Du, and Andy Way. 2017 · 2017
Earlier work this paper cites.
On Internal Language Representations in Deep Learning: An Analysis of Machine Translation and Speech Recognition
Belinkov, Yonatan. 2018 · 2018
Earlier work this paper cites.
What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Conneau, Alexis, German Kruszewski, Guillaume Lample, Loïc Barrault, and Marco Baroni. 2018 · 2018
Earlier work this paper cites.
Under the hood: Using diagnostic classifiers to investigate and improve how language models track agreement information
Giulianelli, Mario, Jack Harding, Florian Mohnert, Dieuwke Hupkes, and Willem Zuidema. 2018 · 2018
Earlier work this paper cites.
Visualisation and ’diagnostic classifiers’ reveal how recurrent and recursive neural networks process hierarchical structure
Hupkes, Dieuwke, Sara Veldhoen, and Willem Zuidema. 2018 · 2018
Earlier work this paper cites.
An analysis of encoder representations in transformer-based machine translation
Raganato, Alessandro and Jörg Tiedemann. 2018 · 2018
Earlier work this paper cites.
Language modeling teaches you more than translation does: Lessons learned through auxiliary syntactic task analysis
Zhang, Kelly and Samuel Bowman. 2018 · 2018
Earlier work this paper cites.
Identifying and controlling important neurons in neural machine translation
Bau, Anthony, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, and James Glass. 2019 · 2019
Cited alongside, same era.
Analysis methods in neural language processing: A survey
Belinkov, Yonatan and James Glass. 2019 · 2019
Cited alongside, same era.
Correlating neural and symbolic representations of language
Chrupała, Grzegorz and Afra Alishahi. 2019 · 2019
Cited alongside, same era.
What does BERT look at? an analysis of BERT’s attention
Clark, Kevin, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Designing and interpreting probes with control tasks
Hewitt, John and Percy Liang. 2019 · 2019
Asking without telling: Exploring latent ontologies in contextual representations
Michael, Julian, Jan A. Botha, and Ian Tenney. 2020 · 2020
Later among the works it cites.
Pareto probing: Trading off accuracy for complexity
Pimentel, Tiago, Naomi Saphra, Adina Williams, and Ryan Cotterell. 2020a · 2020
Later among the works it cites.
A primer in BERTology: What we know about how BERT works
Rogers, Anna, Olga Kovaleva, and Anna Rumshisky. 2020 · 2020
Later among the works it cites.
Investigating transferability in pretrained language models
Tamkin, Alex, Trisha Singh, Davide Giovanardi, and Noah Goodman. 2020 · 2020
Later among the works it cites.
Investigating gender bias in language models using causal mediation analysis
Vig, Jesse, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 2020 · 2020
Later among the works it cites.
Information-theoretic probing with minimum description length
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Hierarchical multitask learning for CTC-based speech recognition
Krishna, Kalpesh, Shubham Toshniwal, and Karen Livescu. 2019 · 2019
Cited alongside, same era.
The emergence of number and syntax units in LSTM language models
Lakretz, Yair, German Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, and Marco Baroni. 2019 · 2019
Cited alongside, same era.
Linguistic knowledge and transferability of contextual representations
Liu, Nelson F., Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith. 2019 · 2019
Cited alongside, same era.
From balustrades to pierre vinken: Looking for syntax in transformer self-attentions
Mareček, David and Rudolf Rosa. 2019 · 2019
Cited alongside, same era.
What do you learn from context? probing for sentence structure in contextualized word representations
Tenney, Ian, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Sam Bowman, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
Cited alongside, same era.
On the linguistic representational power of neural machine translation models
Belinkov, Yonatan, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass. 2020 · 2020
Cited alongside, same era.
Voita, Elena and Ivan Titov. 2020 · 2020
Later among the works it cites.
Interpreting predictions of NLP models
Wallace, Eric, Matt Gardner, and Sameer Singh. 2020 · 2020
Later among the works it cites.
Perturbed masking: Parameter-free probing for analyzing and interpreting BERT
Wu, Zhiyong, Yun Chen, Ben Kao, and Qun Liu. 2020 · 2020
Later among the works it cites.
An information theoretic view on selecting linguistic probes
Zhu, Zining and Frank Rudzicz. 2020 · 2020
Later among the works it cites.
Low-complexity probing via finding subnetworks
Cao, Steven, Victor Sanh, and Alexander Rush. 2021 · 2021
Closest in time.
Amnesic probing: Behavioral explanation with amnesic counterfactuals
Elazar, Yanai, Shauli Ravfogel, Alon Jacovi, and Yoav Goldberg. 2021 · 2021
Closest in time.
CausaLM: Causal Model Explanation Through Counterfactual Language Models
Feder, Amir, Nadav Oved, Uri Shalit, and Roi Reichart. 2021 · 2021
Closest in time.
Predicting inductive biases of pre-trained models
Lovering, Charles, Rohan Jha, Tal Linzen, and Ellie Pavlick. 2021 · 2021
Closest in time.
Probing the probing paradigm: Does probing accuracy entail task relevance?
Ravichander, Abhilasha, Yonatan Belinkov, and Eduard Hovy. 2021 · 2021
Closest in time.
What if this modified that? syntactic interventions with counterfactual embeddings
Tucker, Mycal, Peng Qian, and Roger Levy. 2021 · 2021
Closest in time.
When do you need billions of words of pretraining data?
Zhang, Yian, Alex Warstadt, Xiaocheng Li, and Samuel R. Bowman. 2021 · 2021
Closest in time.
DirectProbe: Studying representations without classifiers
Zhou, Yichu and Vivek Srikumar. 2021 · 2021
Closest in time.
What’s in an embedding? analyzing word embeddings through multilingual evaluation
Köhn, Arne. 2015 · 2073
Closest in time.