Evaluating the State of the Art
By R. Cooper, Dick Crouch. 1995
Subfields: Evaluation & Benchmarks
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Evaluation & Benchmarks
- Sebastian Gehrmann
- Thibault Sellam
- Elizabeth Clark
- Ondrej Dusek
- Verena Rieser
- Anastasia Shimorina
- Shashi Narayan
- Tatsunori B. Hashimoto
Citations in the corpus
- The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics (2021, methodology): “To account for this aspect, we compute multiple diversity metrics, starting with those proposed for the analysis of the results of the E2E NLG challenge (Dusek et al., 2020) and by van Miltenburg et al.”
- Semantic Noise Matters for Neural Natural Language Generation (2019, methodology): “According to Duˇsek et al. (2019), the multiple references should help NLG systems abstract from the noise.”
- Publicly Available Clinical BERT Embeddings (2019, methodology): “On 2 de-identification (de-ID) tasks, i2b2 2006 (Uzuner et al., 2007) and i2b2 2014 (Stubbs et al.”
- In-BoXBART: Get Instructions into Biomedical Multi-Task Learning (2022, methodology): “(Uzuner et al., 2007) to perform this task.”