An Open Intent Discovery Evaluation Framework
(2024)
Presentation / Conference Contribution
Anderson, G., Hart, E., Gkatzia, D., & Beaver, I. (2024, September). An Open Intent Discovery Evaluation Framework. Presented at SIGDIAL 2024, Kyoto, Japan
All Outputs (6)
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
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. Poster presented at INLG 2024, Tokyo, Japan
Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot (2024)
Presentation / Conference Contribution
Wilson, M., Brazier, D., Gkatzia, D., & Robertson, P. (2024, July). Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot. Presented at ACM Conversational User Interfaces 2024 (CUI ’24), Luxembourg, LuxembourgWe present a study of collaboration with expert participants for the purpose of the responsible design of a conversational agent. The Delphi study was used to identify and develop design and evaluation criteria for an automated career support interve... Read More about Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot.
Automated Human-Readable Label Generation in Open Intent Discovery (2024)
Presentation / Conference Contribution
Anderson, G., Hart, E., Gkatzia, D., & Beaver, I. (2024, September). Automated Human-Readable Label Generation in Open Intent Discovery. Presented at Interspeech 2024, Kos, GreeceThe correct determination of user intent is key in dialog systems. However, an intent classifier often requires a large, labelled training dataset to identify a set of known intents. The creation of such a dataset is a complex and time-consuming task... Read More about Automated Human-Readable Label Generation in Open Intent Discovery.
Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation (2024)
Presentation / Conference Contribution
Watson, L. N., & Gkatzia, D. (2024, May). Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation. Presented at HumEval2024 at LREC-COLING 2024, Turin, ItalyReproducibility is a cornerstone of scientific research, ensuring the reliability and generalisability of findings. The ReproNLP Shared Task on Reproducibility of Evaluations in NLP aims to assess the reproducibility of human evaluation studies. This... Read More about Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation.