Outputs (2)

Exploring the impact of data representation on neural data-to-text generation (2024)
Presentation / Conference Contribution
Howcroft, D. M., Watson, L. N., Nedopas, O., & Gkatzia, D. (2024, September). Exploring the impact of data representation on neural data-to-text generation. Presented at INLG 2024, Tokyo, Japan

A relatively under-explored area in research on neural natural language generation is the impact of the data representation on text quality. Here we report experiments on two leading input representations for data-to-text generation: attribute-value... Read More about Exploring the impact of data representation on neural data-to-text generation.

Automatic Metrics in Natural Language Generation: A survey of Current Evaluation Practices (2024)
Presentation / Conference Contribution
Schmidtova, P., Mahamood, S., Balloccu, S., Dusek, O., Gatt, A., Gkatzia, D., Howcroft, D. M., Platek, O., & Sivaprasad, A. (2024, September). Automatic Metrics in Natural Language Generation: A survey of Current Evaluation Practices. Presented at INLG 2024, Tokyo, Japan

Automatic metrics are extensively used to evaluate Natural Language Processing systems. However, there has been increasing focus on how the are used and reported by practitioners within the field. In this paper, we have conducted a survey on the use... Read More about Automatic Metrics in Natural Language Generation: A survey of Current Evaluation Practices.