activity
20142026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 1.2k across the 48 of their papers we have counts for

collaborators
Showing 2022Show all

8 papers · 1 filter

cs.CL2022

POTATO: The Portable Text Annotation Tool

Jiaxin Pei, Aparna Ananthasubramaniam, Xingyao Wang +4

We present POTATO, the Portable text annotation tool, a free, fully open-sourced annotation system that 1) supports labeling many types of text and multimodal data; 2) offers easy-…

cs.CL2022★ 11 cited

A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing

Allison Lahnala, Charles Welch, David Jurgens +1

We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low…

cs.CL2022

Modeling Information Change in Science Communication with Semantically Matched Paraphrases

Dustin Wright, Jiaxin Pei, David Jurgens +1

Whether the media faithfully communicate scientific information has long been a core issue to the science community. Automatically identifying paraphrased scientific findings could…

cs.CL2022★ 2 cited

SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis

Jiaxin Pei, Vítor Silva, Maarten Bos +4

We propose MINT, a new Multilingual INTimacy analysis dataset covering 13,372 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese…

cs.CL2022★ 565 cited

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…

cs.CL2022★ 1 cited

An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications

Sungjin Nam, David Jurgens, Gwen Frishkoff +1

Both humans and machines learn the meaning of unknown words through contextual information in a sentence, but not all contexts are equally helpful for learning. We introduce an eff…

cs.CL2022★ 1 cited

ByT5 model for massively multilingual grapheme-to-phoneme conversion

Jian Zhu, Cong Zhang, David Jurgens

In this study, we tackle massively multilingual grapheme-to-phoneme conversion through implementing G2P models based on ByT5. We have curated a G2P dataset from various sources tha…

cs.SI2022

Networks and Identity Drive Geographic Properties of the Diffusion of Linguistic Innovation

Aparna Ananthasubramaniam, David Jurgens, Daniel M. Romero

Adoption of cultural innovation (e.g., music, beliefs, language) is often geographically correlated, with adopters largely residing within the boundaries of relatively few well-stu…