52 citations · 65 across the 8 of their papers we have counts for
4 papers · 1 filter
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…
Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing
Shailza Jolly, Pepa Atanasova, Isabelle Augenstein
Fact-checking systems have become important tools to verify fake and misguiding news. These systems become more trustworthy when human-readable explanations accompany the veracity…
Search and Learn: Improving Semantic Coverage for Data-to-Text Generation
Shailza Jolly, Zi Xuan Zhang, Andreas Dengel +1
Data-to-text generation systems aim to generate text descriptions based on input data (often represented in the tabular form). A typical system uses huge training samples for learn…
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…