SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors

SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors

18 August 2018

Luis Espinosa-Anke

Steven Schockaert

Papers citing "SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors"

10 / 10 papers shown

Title
TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic Tasks Viktor Moskvoretskii Ekaterina Neminova Alina Lobanova Alexander Panchenko Irina Nikishina 32 6 0 14 Mar 2024
RelBERT: Embedding Relations with Language Models Asahi Ushio Jose Camacho-Collados Steven Schockaert KELM 22 1 0 30 Sep 2023
Distilling Relation Embeddings from Pre-trained Language Models Asahi Ushio Jose Camacho-Collados Steven Schockaert 19 21 0 21 Sep 2021
CORD-19: The COVID-19 Open Research Dataset Lucy Lu Wang Kyle Lo Yoganand Chandrasekhar Russell Reas Jiangjiang Yang ... Boya Xie Douglas A. Raymond Daniel S. Weld Oren Etzioni Sebastian Kohlmeier 37 803 0 22 Apr 2020
Inducing Relational Knowledge from BERT Zied Bouraoui Jose Camacho-Collados Steven Schockaert 15 166 0 28 Nov 2019
Relational Word Embeddings Jose Camacho-Collados Luis Espinosa-Anke Steven Schockaert NAI 17 17 0 04 Jun 2019
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference Mandar Joshi Eunsol Choi Omer Levy Daniel S. Weld Luke Zettlemoyer CoGe 9 47 0 20 Oct 2018
From Word to Sense Embeddings: A Survey on Vector Representations of Meaning Jose Camacho-Collados Mohammad Taher Pilehvar 15 335 0 10 May 2018
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 255 13,364 0 25 Aug 2014
From Frequency to Meaning: Vector Space Models of Semantics Peter D. Turney Patrick Pantel 82 2,980 0 04 Mar 2010