565 citations · 711 across the 35 of their papers we have counts for
4 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…
CANDLE: Decomposing Conditional and Conjunctive Queries for Task-Oriented Dialogue Systems
Aadesh Gupta, Kaustubh D. Dhole, Rahul Tarway +2
Domain-specific dialogue systems generally determine user intents by relying on sentence level classifiers that mainly focus on single action sentences. Such classifiers are not de…
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
Simon Mille, Kaustubh D. Dhole, Saad Mahamood +5
Machine learning approaches applied to NLP are often evaluated by summarizing their performance in a single number, for example accuracy. Since most test sets are constructed as an…
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…