1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2022
Text Characterization Toolkit
Daniel Simig, Tianlu Wang, Verna Dankers +4
In NLP, models are usually evaluated by reporting single-number performance scores on a number of readily available benchmarks, without much deeper analysis. Here, we argue that -…
cs.CL2022★ 1 cited
Open Vocabulary Extreme Classification Using Generative Models
Daniel Simig, Fabio Petroni, Pouya Yanki +4
The extreme multi-label classification (XMC) task aims at tagging content with a subset of labels from an extremely large label set. The label vocabulary is typically defined in ad…