Towards Neuro-Symbolic Approaches for Referring Expression Generation
Manar Ali, Marika Sarzotti, Simeon Junker, Hendrik Buschmeier, Sina Zarrieß
Abstract
Referring Expression Generation (REG) has a long-standing tradition in computational linguistics, and often aims to develop cognitively plausible models of language generation and dialogue modeling, in a multimodal context. Traditional approaches to reference have been mostly symbolic, recent ones have been mostly neural. Inspired by the recent interest in neuro-symbolic approaches in both fields – language and vision – we revisit REG from these perspectives. We review relevant neuro-symbolic approaches to language generation on the one hand and vision on the other hand, exploring possible future directions for cognitively plausible models of reference generation/reference game modeling.- Anthology ID:
- 2025.clasp-main.4
- Volume:
- Proceedings of the 2025 CLASP Conference on Language models And RePresentations (LARP)
- Month:
- September
- Year:
- 2025
- Address:
- Gothenburg, Sweden
- Editors:
- Nikolai Ilinykh, Mattias Appelgren, Erik Lagerstedt
- Venues:
- CLASP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 38–50
- Language:
- URL:
- https://preview.aclanthology.org/tal-24-ingestion/2025.clasp-main.4/
- DOI:
- Cite (ACL):
- Manar Ali, Marika Sarzotti, Simeon Junker, Hendrik Buschmeier, and Sina Zarrieß. 2025. Towards Neuro-Symbolic Approaches for Referring Expression Generation. In Proceedings of the 2025 CLASP Conference on Language models And RePresentations (LARP), pages 38–50, Gothenburg, Sweden. Association for Computational Linguistics.
- Cite (Informal):
- Towards Neuro-Symbolic Approaches for Referring Expression Generation (Ali et al., CLASP 2025)
- PDF:
- https://preview.aclanthology.org/tal-24-ingestion/2025.clasp-main.4.pdf