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The POLAR Framework: Polar Opposites Enable Interpretability of
  Pre-Trained Word Embeddings
v1v2 (latest)

The POLAR Framework: Polar Opposites Enable Interpretability of Pre-Trained Word Embeddings

The Web Conference (WWW), 2020
27 January 2020
Binny Mathew
Sandipan Sikdar
Florian Lemmerich
M. Strohmaier
ArXiv (abs)PDFHTML

Papers citing "The POLAR Framework: Polar Opposites Enable Interpretability of Pre-Trained Word Embeddings"

18 / 18 papers shown
Profiling Bias in LLMs: Stereotype Dimensions in Contextual Word Embeddings
Profiling Bias in LLMs: Stereotype Dimensions in Contextual Word Embeddings
Carolin M. Schuster
Maria-Alexandra Dinisor
Shashwat Ghatiwala
Georg Groh
463
4
0
25 Nov 2024
Rethinking Node Representation Interpretation through Relation Coherence
Rethinking Node Representation Interpretation through Relation Coherence
Ying-Chun Lin
Jennifer Neville
Cassiano Becker
Purvanshi Metha
Nabiha Asghar
Vipul Agarwal
220
0
0
01 Nov 2024
Disentangling Hate Across Target Identities
Disentangling Hate Across Target Identities
Yiping Jin
Leo Wanner
Aneesh Moideen Koya
264
1
0
14 Oct 2024
Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed
  Embeddings
Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Hiroaki Yamagiwa
Yusuke Takase
Hidetoshi Shimodaira
271
4
0
11 Jan 2024
Discovering Universal Geometry in Embeddings with ICA
Discovering Universal Geometry in Embeddings with ICAConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Hiroaki Yamagiwa
Momose Oyama
Hidetoshi Shimodaira
264
20
0
22 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Similarity of Neural Network Models: A Survey of Functional and Representational MeasuresACM Computing Surveys (ACM Comput. Surv.), 2023
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
708
132
0
10 May 2023
SensePOLAR: Word sense aware interpretability for pre-trained contextual
  word embeddings
SensePOLAR: Word sense aware interpretability for pre-trained contextual word embeddingsConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Jan Engler
Sandipan Sikdar
Marlene Lutz
M. Strohmaier
257
10
0
11 Jan 2023
Explainability of Text Processing and Retrieval Methods: A Survey
Explainability of Text Processing and Retrieval Methods: A Survey
Sourav Saha
Debapriyo Majumdar
Mandar Mitra
374
5
0
14 Dec 2022
Discovering Differences in the Representation of People using
  Contextualized Semantic Axes
Discovering Differences in the Representation of People using Contextualized Semantic AxesConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
L. Lucy
Divya Tadimeti
David Bamman
290
15
0
21 Oct 2022
Lex2Sent: A bagging approach to unsupervised sentiment analysis
Lex2Sent: A bagging approach to unsupervised sentiment analysisConference on Natural Language Processing (NLP), 2022
Kai-Robin Lange
Jonas Rieger
Carsten Jentsch
SSL
174
6
0
26 Sep 2022
Interpreting Embedding Spaces by Conceptualization
Interpreting Embedding Spaces by ConceptualizationConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Adi Simhi
Shaul Markovitch
321
13
0
22 Aug 2022
The Need for Interpretable Features: Motivation and Taxonomy
The Need for Interpretable Features: Motivation and TaxonomySIGKDD Explorations (SIGKDD Explor.), 2022
Alexandra Zytek
Ignacio Arnaldo
Dongyu Liu
Laure Berti-Equille
K. Veeramachaneni
FAttXAI
241
18
0
23 Feb 2022
Interpretable contrastive word mover's embedding
Interpretable contrastive word mover's embedding
Ruijie Jiang
J. Gouvea
Preetish Rath
David M. Hammer
Shuchin Aeron
291
2
0
01 Nov 2021
Understanding and Countering Stereotypes: A Computational Approach to
  the Stereotype Content Model
Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content ModelAnnual Meeting of the Association for Computational Linguistics (ACL), 2021
Kathleen C. Fraser
I. Nejadgholi
S. Kiritchenko
245
52
0
04 Jun 2021
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for
  Post-Hoc Interpretability
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability
Ninghao Liu
Yunsong Meng
Helen Zhou
Tie Wang
Bo Long
XAIFAtt
214
7
0
16 Sep 2020
Adversarial Attacks and Defenses: An Interpretation Perspective
Adversarial Attacks and Defenses: An Interpretation Perspective
Ninghao Liu
Mengnan Du
Ruocheng Guo
Huan Liu
Helen Zhou
AAML
246
8
0
23 Apr 2020
Word Equations: Inherently Interpretable Sparse Word Embeddingsthrough
  Sparse Coding
Word Equations: Inherently Interpretable Sparse Word Embeddingsthrough Sparse CodingBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP), 2020
Adly Templeton
359
7
0
08 Apr 2020
FrameAxis: Characterizing Microframe Bias and Intensity with Word
  Embedding
FrameAxis: Characterizing Microframe Bias and Intensity with Word EmbeddingPeerJ Computer Science (PeerJ Comput. Sci.), 2020
Haewoon Kwak
Jisun An
Elise Jing
Yong-Yeol Ahn
335
50
0
20 Feb 2020
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