activity
20202026
most citedData and its (dis)contents: A survey of dataset development and use in machine learning research

61 citations · 78 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2026

Recognizing Atari and Assessing Sente: Controlled Evaluation Tasks for Language-Based Go Agents

Taiyi Chen, Iskar Deng, Amandalynne Paullada

Domain terminology provides concise descriptions of game states and strategic relationships, but whether game-playing language models can accurately recognize these concepts and re…

cs.CL2026

Before the Labels: How Dataset Construction Shapes Suicidality Detection in Clinical Text

Priyanshi Garg, Ishita Rao, Jieqiong Ding +1

Clinical NLP increasingly relies on electronic health record (EHR) data to detect suicidal behaviors, treating clinical documentation as more reliable ground truth than social medi…

cs.CL2022★ 2 cited

Behind the Mask: Demographic bias in name detection for PII masking

Courtney Mansfield, Amandalynne Paullada, Kristen Howell

Many datasets contain personally identifiable information, or PII, which poses privacy risks to individuals. PII masking is commonly used to redact personal information such as nam…

cs.LG2021★ 15 cited

AI and the Everything in the Whole Wide World Benchmark

Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada +2

There is a tendency across different subfields in AI to valorize a small collection of influential benchmarks. These benchmarks operate as stand-ins for a range of anointed common…

cs.CL2021

A multilabel approach to morphosyntactic probing

Naomi Tachikawa Shapiro, Amandalynne Paullada, Shane Steinert-Threlkeld

We introduce a multilabel probing task to assess the morphosyntactic representations of word embeddings from multilingual language models. We demonstrate this task with multilingua…

cs.LG2020★ 61 cited

Data and its (dis)contents: A survey of dataset development and use in machine learning research

Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender +2

Datasets have played a foundational role in the advancement of machine learning research. They form the basis for the models we design and deploy, as well as our primary medium for…