activity
20182021
most citedThe GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

52 citations · 64 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL202152 cited

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53

We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…

cs.CL20208 cited

A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation

Moin Nadeem, Tianxing He, Kyunghyun Cho +1

This work studies the widely adopted ancestral sampling algorithms for auto-regressive language models, which is not widely studied in the literature. We use the quality-diversity…

cs.CL2020

StereoSet: Measuring stereotypical bias in pretrained language models

Moin Nadeem, Anna Bethke, Siva Reddy

A stereotype is an over-generalized belief about a particular group of people, e.g., Asians are good at math or Asians are bad drivers. Such beliefs (biases) are known to hurt targ…

cs.CL20194 cited

FAKTA: An Automatic End-to-End Fact Checking System

Moin Nadeem, Wei Fang, Brian Xu +2

We present FAKTA which is a unified framework that integrates various components of a fact checking process: document retrieval from media sources with various types of reliability…

cs.IR2018

Context-Aware Systems for Sequential Item Recommendation

Moin Nadeem, Dustin Stansbury, Shane Mooney

Quizlet is the most popular online learning tool in the United States, and is used by over 2/3 of high school students, and 1/2 of college students. With more than 95% of Quizlet u…

cs.NI2018

Automating Network Error Detection using Long-Short Term Memory Networks

Moin Nadeem, Vibhor Nigam, Dimosthenis Anagnostopoulos +1

In this work, we investigate the current flaws with identifying network-related errors, and examine how K-Means and Long-Short Term Memory Networks solve these problems. We demonst…