Using dependency parsing for few-shot learning in distributional semantics

12 May 2022

Papers citing "Using dependency parsing for few-shot learning in distributional semantics"

11 / 11 papers shown

Title
Representing Syntax and Composition with Geometric Transformations Lorenzo Bertolini Julie Weeds David J. Weir Qiwei Peng 47 2 0 03 Jun 2021
True Few-Shot Learning with Language Models Ethan Perez Douwe Kiela Kyunghyun Cho 135 439 0 24 May 2021
What are the Goals of Distributional Semantics? Guy Edward Toh Emerson 60 26 0 06 May 2020
Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models Jeroen Van Hautte Guy Edward Toh Emerson Marek Rei 33 4 0 01 Oct 2019
Distributional Semantics and Linguistic Theory Gemma Boleda 74 202 0 06 May 2019
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context Timo Schick Hinrich Schütze AI4TS NAI 74 34 0 09 Nov 2018
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors M. Khodak Nikunj Saunshi Yingyu Liang Tengyu Ma Brandon M Stewart Sanjeev Arora 85 100 0 14 May 2018
High-risk learning: acquiring new word vectors from tiny data Aurélie Herbelot Marco Baroni 43 83 0 20 Jul 2017
Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling Diego Marcheggiani Ivan Titov GNN NAI 80 832 0 14 Mar 2017
Enriching Word Vectors with Subword Information Piotr Bojanowski Edouard Grave Armand Joulin Tomas Mikolov NAI SSL VLM 229 9,978 0 15 Jul 2016
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 399 33,550 0 16 Oct 2013