nyu-mll/crows-pairs nyu-mll/crows-pairs

  • Stars
    star
    99
  • Rank 343,315 (Top 7 %)
  • Language
    HTML
  • Created over 4 years ago
  • Updated 8 months ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
nyu-mll/crows-pairs
github

nyu-mll

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

This repository contains the data and code introduced in the paper "CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models" (EMNLP 2020).

More Repositories

1

jiant

jiant is an nlp toolkit
Python
1,639
star
2

GLUE-baselines

[DEPRECATED] Repo for exploring multi-task learning approaches to learning sentence representations
Python
762
star
3

multiNLI

Python
209
star
4

quality

Python
119
star
5

BBQ

Repository for the Bias Benchmark for QA dataset.
Python
85
star
6

DS-GA-1011-Fall2017

DS-GA-1011 Natural Language Processing with Representation Learning
Jupyter Notebook
81
star
7

ILF-for-code-generation

Python
68
star
8

CoLA-baselines

Baselines and corpus accompanying paper Neural Network Acceptability Judgments
Python
55
star
9

PRPN-Analysis

This repo contains the analysis results reported in the paper "Grammar Induction with Neural Language Models: An Unusual Replication"
Python
47
star
10

SQuALITY

Query-focused summarization data
Python
40
star
11

jiant-v1-legacy

The jiant toolkit for general-purpose text understanding models
Jupyter Notebook
21
star
12

pretraining-learning-curves

The repository for the paper "When Do You Need Billions of Words of Pretraining Data?"
20
star
13

msgs

This is a repository for the paper on testing inductive bias with scaled-down RoBERTa models.
Python
19
star
14

nlu-test-sets

Analysis of NLU test sets with IRT
Jupyter Notebook
10
star
15

CoLA

Demo for Grammaticality Judgement (Acceptability) task
JavaScript
7
star
16

nope

Data and code for "NOPE: A Corpus of Naturally-Occurring Presuppositions in English."
TeX
7
star
17

semi-automatic-nli

This is a repository for data and code accompanying paper "Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options" (AACL 2020)
Python
6
star
18

online-code-for-edge-probing

Jupyter Notebook
5
star
19

wsc-formalizations

Jupyter Notebook
4
star
20

crowdsourcing-protocol-comparison

HTML
3
star
21

CNLI-generalization

Python
2
star
22

GLUE-human-performance

HTML
1
star
23

nyu-ai-school-2023

HTML
1
star