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Not All Models Localize Linguistic Knowledge in the Same Place: A
  Layer-wise Probing on BERToids' Representations

Not All Models Localize Linguistic Knowledge in the Same Place: A Layer-wise Probing on BERToids' Representations

13 September 2021
Mohsen Fayyaz
Ehsan Aghazadeh
Ali Modarressi
Hosein Mohebbi
Mohammad Taher Pilehvar
ArXivPDFHTML

Papers citing "Not All Models Localize Linguistic Knowledge in the Same Place: A Layer-wise Probing on BERToids' Representations"

14 / 14 papers shown
Title
Linguistic Interpretability of Transformer-based Language Models: a systematic review
Linguistic Interpretability of Transformer-based Language Models: a systematic review
Miguel López-Otal
Jorge Gracia
Jordi Bernad
Carlos Bobed
Lucía Pitarch-Ballesteros
Emma Anglés-Herrero
VLM
84
0
0
09 Apr 2025
Inspecting the concept knowledge graph encoded by modern language models
Inspecting the concept knowledge graph encoded by modern language models
Carlos Aspillaga
Marcelo Mendoza
Alvaro Soto
56
13
0
27 May 2021
What Happens To BERT Embeddings During Fine-tuning?
What Happens To BERT Embeddings During Fine-tuning?
Amil Merchant
Elahe Rahimtoroghi
Ellie Pavlick
Ian Tenney
59
186
0
29 Apr 2020
Analyzing analytical methods: The case of phonology in neural models of
  spoken language
Analyzing analytical methods: The case of phonology in neural models of spoken language
Grzegorz Chrupała
Bertrand Higy
Afra Alishahi
37
20
0
15 Apr 2020
What's so special about BERT's layers? A closer look at the NLP pipeline
  in monolingual and multilingual models
What's so special about BERT's layers? A closer look at the NLP pipeline in monolingual and multilingual models
Wietse de Vries
Andreas van Cranenburgh
Malvina Nissim
MILM
SSeg
MoE
95
64
0
14 Apr 2020
oLMpics -- On what Language Model Pre-training Captures
oLMpics -- On what Language Model Pre-training Captures
Alon Talmor
Yanai Elazar
Yoav Goldberg
Jonathan Berant
LRM
79
303
0
31 Dec 2019
The Bottom-up Evolution of Representations in the Transformer: A Study
  with Machine Translation and Language Modeling Objectives
The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives
Elena Voita
Rico Sennrich
Ivan Titov
252
186
0
03 Sep 2019
What do you learn from context? Probing for sentence structure in
  contextualized word representations
What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney
Patrick Xia
Berlin Chen
Alex Jinpeng Wang
Adam Poliak
...
Najoung Kim
Benjamin Van Durme
Samuel R. Bowman
Dipanjan Das
Ellie Pavlick
163
853
0
15 May 2019
BERT Rediscovers the Classical NLP Pipeline
BERT Rediscovers the Classical NLP Pipeline
Ian Tenney
Dipanjan Das
Ellie Pavlick
MILM
SSeg
109
1,458
0
15 May 2019
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Zihang Dai
Zhilin Yang
Yiming Yang
J. Carbonell
Quoc V. Le
Ruslan Salakhutdinov
VLM
163
3,714
0
09 Jan 2019
Neural Network Acceptability Judgments
Neural Network Acceptability Judgments
Alex Warstadt
Amanpreet Singh
Samuel R. Bowman
194
1,390
0
31 May 2018
What you can cram into a single vector: Probing sentence embeddings for
  linguistic properties
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
Germán Kruszewski
Guillaume Lample
Loïc Barrault
Marco Baroni
295
888
0
03 May 2018
Deep contextualized word representations
Deep contextualized word representations
Matthew E. Peters
Mark Neumann
Mohit Iyyer
Matt Gardner
Christopher Clark
Kenton Lee
Luke Zettlemoyer
NAI
143
11,520
0
15 Feb 2018
A Broad-Coverage Challenge Corpus for Sentence Understanding through
  Inference
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams
Nikita Nangia
Samuel R. Bowman
456
4,444
0
18 Apr 2017
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