Overview and Joint Report of the Robustness and Consistency Task of the ELOQUENT 2025 Lab for Evaluating Generative Language Model Quality Notebook for the ELOQUENT Lab at CLEF 2025

Open Access
Authors
  • Jussi Karlgren
  • Marie Isabel Engels
  • Maria Barrett
  • Rohit Raj Gunti
Publication date 2025
Host editors
  • G. Faggioli
  • N. Ferro
  • P. Rosso
  • D. Spina
Book title Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2025)
Book subtitle Madrid, Spain, 9-12 September 2025
Series CEUR Workshop Proceedings
Event 26th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2025
Pages (from-to) 1306-1319
Number of pages 14
Publisher Aachen: CEUR-WS
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract

Generative language models are intended to be creative and responsive to the style of the conversation they engage in. The experimental Robustness and Consistency task is designed to explore how variation between content-wise equivalent inputs influences the output of a generative language model, and in this year’s edition the task focuses on how linguistic variation makes a difference for value-oriented questions. This paper is a joint report by all participants in the task.

Document type Conference contribution
Language English
Published at https://ceur-ws.org/Vol-4038/paper_104.pdf
Other links https://ceur-ws.org/Vol-4038/ https://www.scopus.com/pages/publications/105019040432
Downloads
paper_104 (Final published version)
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