Lost in Context? On the Sense-wise Variance of Contextualized Word
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Lost in Context? On the Sense-wise Variance of Contextualized Word Embeddings

20 August 2022

Yue Zhang

Papers citing "Lost in Context? On the Sense-wise Variance of Contextualized Word Embeddings"

7 / 7 papers shown

Title
Let's Play Mono-Poly: BERT Can Reveal Words' Polysemy Level and Partitionability into Senses Aina Garí Soler Marianna Apidianaki MILM 201 68 0 29 Apr 2021
Measuring and Improving Consistency in Pretrained Language Models Yanai Elazar Nora Kassner Shauli Ravfogel Abhilasha Ravichander Eduard H. Hovy Hinrich Schütze Yoav Goldberg HILM 258 346 0 01 Feb 2021
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 408 2,584 0 03 Sep 2019
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 199 882 0 03 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,950 0 20 Apr 2018
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,253 0 16 Jan 2013