Abstract
Natural Language Generation (NLG) evaluation has changed dramatically since 1990, and will continue to evolve in the future. In 1990, when NLG had close ties to linguistics, there was very little formal experimental evaluation in the modern sense. In 2026, when NLG is closely linked to machine learning, experimental evaluation is expected and indeed fundamental to research. Many evaluation techniques were developed over this period, including most recently LLM-as-Judge. I expect NLG evaluation will continue to evolve in the future. In particular, impact, qualitative, and safety evaluation will become more important as large numbers of people routinely use NLG technology.
- Anthology ID:
- 2026.retroeval-main.2
- Volume:
- Proceedings of the 1st Symposium on Natural Language Generation Evaluations
- Month:
- June
- Year:
- 2026
- Address:
- Aberdeen, United Kingdom
- Editors:
- Saad Mahamood, David M. Howcroft, Kees van Deemter, Simone Balloccu, Adarsa Sivaprasad, Barkavi Sundararajan, Alberto Bugarín Diz, Jose María Alonso-Moral
- Venue:
- RetroEval
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8–15
- Language:
- URL:
- https://aclanthology.org/2026.retroeval-main.2/
- DOI:
- Bibkey:
- Cite (ACL):
- Ehud Reiter. 2026. NLG Evaluation: Past, Present, Future. In Proceedings of the 1st Symposium on Natural Language Generation Evaluations, pages 8–15, Aberdeen, United Kingdom. Association for Computational Linguistics.
- Cite (Informal):
- NLG Evaluation: Past, Present, Future (Reiter, RetroEval 2026)
- Copy Citation:
- PDF:
- https://aclanthology.org/2026.retroeval-main.2.pdf