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20182023
most citedThe GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

52 citations · 109 across the 17 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CL2022★ 1 cited

Needle in a Haystack: An Analysis of High-Agreement Workers on MTurk for Summarization

Lining Zhang, Simon Mille, Yufang Hou +8

To prevent the costly and inefficient use of resources on low-quality annotations, we want a method for creating a pool of dependable annotators who can effectively complete diffic…

cs.CL2022★ 1 cited

CiteBench: A benchmark for Scientific Citation Text Generation

Martin Funkquist, Ilia Kuznetsov, Yufang Hou +1

Science progresses by building upon the prior body of knowledge documented in scientific publications. The acceleration of research makes it hard to stay up-to-date with the recent…

cs.CL2022★ 2 cited

Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for Misinformation

Max Glockner, Yufang Hou, Iryna Gurevych

Misinformation emerges in times of uncertainty when credible information is limited. This is challenging for NLP-based fact-checking as it relies on counter-evidence, which may not…

cs.CL2022★ 3 cited

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…

cs.CL2022★ 42 cited

Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-Centric Summarization

Zhenjie Zhao, Yufang Hou, Dakuo Wang +3

Generating educational questions of fairytales or storybooks is vital for improving children's literacy ability. However, it is challenging to generate questions that capture the i…