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A Latent Variable Model Approach to PMI-based Word Embeddings
v1v2v3v4v5v6v7v8 (latest)

A Latent Variable Model Approach to PMI-based Word Embeddings

12 February 2015
Sanjeev Arora
Yuanzhi Li
Yingyu Liang
Tengyu Ma
Andrej Risteski
ArXiv (abs)PDFHTML

Papers citing "A Latent Variable Model Approach to PMI-based Word Embeddings"

28 / 28 papers shown
The cell as a token: high-dimensional geometry in language models and cell embeddings
The cell as a token: high-dimensional geometry in language models and cell embeddingsBioinformatics (Bioinformatics), 2025
William Gilpin
485
1
0
26 Mar 2025
On the Origins of Linear Representations in Large Language Models
On the Origins of Linear Representations in Large Language Models
Yibo Jiang
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
Victor Veitch
307
61
0
06 Mar 2024
Stable Anisotropic Regularization
Stable Anisotropic RegularizationInternational Conference on Learning Representations (ICLR), 2023
William Rudman
Carsten Eickhoff
409
12
0
30 May 2023
Reliable Measures of Spread in High Dimensional Latent Spaces
Reliable Measures of Spread in High Dimensional Latent SpacesInternational Conference on Machine Learning (ICML), 2022
Anna C. Marbut
Katy McKinney-Bock
Travis J. Wheeler
418
5
0
15 Dec 2022
IsoScore: Measuring the Uniformity of Embedding Space Utilization
IsoScore: Measuring the Uniformity of Embedding Space Utilization
William Rudman
Nate Gillman
T. Rayne
Carsten Eickhoff
277
42
0
16 Aug 2021
On the Inductive Bias of Masked Language Modeling: From Statistical to
  Syntactic Dependencies
On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic DependenciesNorth American Chapter of the Association for Computational Linguistics (NAACL), 2021
Tianyi Zhang
Tatsunori Hashimoto
AI4CE
262
30
0
12 Apr 2021
Do We Need Online NLU Tools?
Do We Need Online NLU Tools?Language Resources and Evaluation (LRE), 2020
Petr Lorenc
Petro Marek
Jan Pichl
Jakub Konrád
Jan Sedivý
218
6
0
19 Nov 2020
Semantic Holism and Word Representations in Artificial Neural Networks
Semantic Holism and Word Representations in Artificial Neural Networks
Tomáš Musil
MILMNAI
69
1
0
11 Mar 2020
The Spectral Underpinning of word2vec
The Spectral Underpinning of word2vecFrontiers in Applied Mathematics and Statistics (FAMS), 2020
Ariel Jaffe
Y. Kluger
Ofir Lindenbaum
J. Patsenker
Erez Peterfreund
Stefan Steinerberger
379
9
0
27 Feb 2020
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning
Humpty Dumpty: Controlling Word Meanings via Corpus PoisoningIEEE Symposium on Security and Privacy (S&P), 2020
R. Schuster
Tal Schuster
Yoav Meri
Vitaly Shmatikov
AAML
269
42
0
14 Jan 2020
Structured Embedding Models for Grouped Data
Structured Embedding Models for Grouped Data
Maja R. Rudolph
Francisco J. R. Ruiz
Susan Athey
David M. Blei
252
37
0
28 Sep 2017
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of
  some Practical Aspects
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects
Pedro Saleiro
L. Sarmento
E. M. Rodrigues
Carlos Soares
Eugénio C. Oliveira
125
5
0
04 Sep 2017
Representing Sentences as Low-Rank Subspaces
Representing Sentences as Low-Rank Subspaces
Jiaqi Mu
S. Bhat
Pramod Viswanath
343
27
0
18 Apr 2017
Dynamic Word Embeddings for Evolving Semantic Discovery
Dynamic Word Embeddings for Evolving Semantic Discovery
Zijun Yao
Yifan Sun
Weicong Ding
Nikhil S. Rao
Hui Xiong
AI4TS
252
229
0
02 Mar 2017
Using a Distributional Semantic Vector Space with a Knowledge Base for
  Reasoning in Uncertain Conditions
Using a Distributional Semantic Vector Space with a Knowledge Base for Reasoning in Uncertain Conditions
D. Summers-Stay
Clare R. Voss
Taylor Cassidy
96
11
0
13 Jun 2016
Multi-Label Zero-Shot Learning via Concept Embedding
Multi-Label Zero-Shot Learning via Concept Embedding
Ubai Sandouk
Ke Chen
VLM
207
18
0
01 Jun 2016
On the Convergent Properties of Word Embedding Methods
On the Convergent Properties of Word Embedding Methods
Yingtao Tian
Vivek Kulkarni
Bryan Perozzi
Steven Skiena
113
4
0
12 May 2016
Semantic Regularities in Document Representations
Semantic Regularities in Document Representations
Fei Sun
Jiafeng Guo
Yanyan Lan
Jun Xu
Xueqi Cheng
NAI
144
8
0
24 Mar 2016
Enabling Cognitive Intelligence Queries in Relational Databases using
  Low-dimensional Word Embeddings
Enabling Cognitive Intelligence Queries in Relational Databases using Low-dimensional Word Embeddings
R. Bordawekar
O. Shmueli
161
19
0
23 Mar 2016
Recovering Structured Probability Matrices
Recovering Structured Probability Matrices
Qingqing Huang
Sham Kakade
Weihao Kong
Gregory Valiant
668
12
0
21 Feb 2016
From Word Embeddings to Item Recommendation
From Word Embeddings to Item Recommendation
Makbule Gülçin Özsoy
GNN
220
109
0
07 Jan 2016
On the Linear Algebraic Structure of Distributed Word Representations
On the Linear Algebraic Structure of Distributed Word Representations
L. Lee
68
5
0
22 Nov 2015
Controlled Experiments for Word Embeddings
Controlled Experiments for Word Embeddings
Benjamin J. Wilson
A. Schakel
135
29
0
09 Oct 2015
Word, graph and manifold embedding from Markov processes
Word, graph and manifold embedding from Markov processes
Tatsunori B. Hashimoto
David Alvarez-Melis
Tommi Jaakkola
89
10
0
18 Sep 2015
Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility
  of Vector Differences for Lexical Relation Learning
Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning
Ekaterina Vylomova
Laura Rimell
Trevor Cohn
Timothy Baldwin
271
155
0
05 Sep 2015
A Generative Word Embedding Model and its Low Rank Positive Semidefinite
  Solution
A Generative Word Embedding Model and its Low Rank Positive Semidefinite SolutionConference on Empirical Methods in Natural Language Processing (EMNLP), 2015
Shaohua Li
Jun Zhu
Chunyan Miao
239
29
0
16 Aug 2015
WordRank: Learning Word Embeddings via Robust Ranking
WordRank: Learning Word Embeddings via Robust RankingConference on Empirical Methods in Natural Language Processing (EMNLP), 2015
Shihao Ji
Hyokun Yun
Pinar Yanardag
Shin Matsushima
S.V.N. Vishwanathan
OffRL
257
38
0
09 Jun 2015
Text Segmentation based on Semantic Word Embeddings
Text Segmentation based on Semantic Word Embeddings
Alexander A. Alemi
P. Ginsparg
3DV
245
59
0
18 Mar 2015
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