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Abstract
Chatbots for customer service have been widely studied in many different fields, ranging from Natural Language Processing (NLP) to Communication Science. These fields have developed different evaluation practices to assess chatbot performance (e.g., fluency, task success) and to measure the impact of chatbot usage on the user's perception of the organisation controlling the chatbot (e.g., brand attitude) as well as their willingness to enter a business transaction or to continue to use the chatbot in the future (i.e., purchase intention, reuse intention). While NLP researchers have developed many automatic measures of success, other fields mainly use questionnaires to compare different chatbots. This paper explores the extent to which we can bridge the gap between the two, and proposes a research agenda to further explore this question.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM²) |
| Editors | Kaustubh Dhole, Miruna Clinciu |
| Place of Publication | Vienna, Austria and virtual meeting |
| Publisher | Association for Computational Linguistics |
| Pages | 231-238 |
| Number of pages | 8 |
| ISBN (Print) | 979-8-89176-261-9 |
| Publication status | Published - 1 Jul 2025 |
| Event | 4th Workshop on Generation, Evaluation, and Metrics - The Austria Center Vienna (hybrid), Vienna, Austria Duration: 31 Jul 2025 → 1 Aug 2025 https://gem-benchmark.com/workshop |
Conference
| Conference | 4th Workshop on Generation, Evaluation, and Metrics |
|---|---|
| Abbreviated title | GEM 2025 |
| Country/Territory | Austria |
| City | Vienna |
| Period | 31/07/25 → 1/08/25 |
| Internet address |
Keywords
- natural language generation
- evaluation metrics
- prompt engineering
- benchmarking
- model assessment
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Dive into the research topics of 'Measure only what is measurable: Towards conversation requirements for evaluating task-oriented dialogue systems'. Together they form a unique fingerprint.Projects
- 1 Finished
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Smooth Operator. Development and effects of personalized conversational AI.
Liebrecht, C. (Principal Investigator), van Hooijdonk, C. M. J. (CoPI), Krahmer, E. (CoPI), van Miltenburg, E. (CoPI), Kunneman, F. (CoPI), Hoeken, H. (CoPI) & te Molder, H. (CoPI)
31/03/21 → 31/03/25
Project: Research project
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