Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell

5 September 2018

Papers citing "Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell"

11 / 11 papers shown

Title
Seeing What Tastes Good: Revisiting Multimodal Distributional Semantics in the Billion Parameter Era Dan Oneaţă Desmond Elliott Stella Frank 61 0 0 04 Jun 2025
Better Hit the Nail on the Head than Beat around the Bush: Removing Protected Attributes with a Single Projection P. Haghighatkhah Antske Fokkens Pia Sommerauer Bettina Speckmann Kevin Verbeek 83 14 0 08 Dec 2022
COMPS: Conceptual Minimal Pair Sentences for testing Robust Property Knowledge and its Inheritance in Pre-trained Language Models Kanishka Misra Julia Taylor Rayz Allyson Ettinger 121 10 0 05 Oct 2022
Interpreting Embedding Spaces by Conceptualization Adi Simhi Shaul Markovitch 85 7 0 22 Aug 2022
Local Interpretations for Explainable Natural Language Processing: A Survey Siwen Luo Hamish Ivison S. Han Josiah Poon MILM 120 50 0 20 Mar 2021
On the Learnability of Concepts: With Applications to Comparing Word Embedding Algorithms Adam Sutton N. Cristianini 52 8 0 17 Jun 2020
Probing Neural Language Models for Human Tacit Assumptions Nathaniel Weir Adam Poliak Benjamin Van Durme 62 6 0 10 Apr 2020
Feature2Vec: Distributional semantic modelling of human property knowledge Steven Derby Paul Miller Barry Devereux 28 18 0 29 Aug 2019
Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop Afra Alishahi Grzegorz Chrupała Tal Linzen NAI MILM 87 65 0 05 Apr 2019
Neural Vector Conceptualization for Word Vector Space Interpretation Robert Schwarzenberg Lisa Raithel David Harbecke LLMSV VLM 42 10 0 02 Apr 2019
Instantiation Abhijeet Gupta Gemma Boleda Sebastian Padó 37 8 0 05 Aug 2018