2.1k citations · 3.5k across the 25 of their papers we have counts for
8 papers · 1 filter
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
LMdiff: A Visual Diff Tool to Compare Language Models
Hendrik Strobelt, Benjamin Hoover, Arvind Satyanarayan +1
While different language models are ubiquitous in NLP, it is hard to contrast their outputs and identify which contexts one can handle better than the other. To address this questi…
SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets
Ann Yuan, Daphne Ippolito, Vitaly Nikolaev +3
NLP researchers need more, higher-quality text datasets. Human-labeled datasets are expensive to collect, while datasets collected via automatic retrieval from the web such as Wiki…
Learning Compact Metrics for MT
Amy Pu, Hyung Won Chung, Ankur P. Parikh +2
Recent developments in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, which treat evaluation as a regre…
Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards
Angelina McMillan-Major, Salomey Osei, Juan Diego Rodriguez +3
Developing documentation guidelines and easy-to-use templates for datasets and models is a challenging task, especially given the variety of backgrounds, skills, and incentives of…
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann +3
Targeted syntactic evaluations have demonstrated the ability of language models to perform subject-verb agreement given difficult contexts. To elucidate the mechanisms by which the…