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arXiv · 2512.02791

Making Dialogue Grounding Data Rich: A Three-Tier Data Synthesis Framework for Generalized Referring Expression Comprehension

Juexi Shao·Siyou Li·Yujian Gan·Chris Madge·Vanja Karan·Massimo Poesio
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Abstract

Dialogue-Based Generalized Referring Expression Comprehension (GREC) requires models to ground the expression and unlimited targets in complex visual scenes while resolving coreference across a long dialogue context. However, existing systems struggle under distribution shift between training and evaluation domains, a gap exacerbated by the scarcity of annotated dialogue grounding data. We address this challenge with a three-tier data-synthesis method that balances realism and controllability to produce scalable supervision for dialogue-conditioned grounding. Fine-tuning on the synthesized data yields consistent, substantial improvements over prior approaches across standard evaluation metrics.

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Juexi Shao, Siyou Li, Yujian Gan, Chris Madge, Vanja Karan, Massimo Poesio. 2025-12-02. Making Dialogue Grounding Data Rich: A Three-Tier Data Synthesis Framework for Generalized Referring Expression Comprehension. https://doi.org/10.1109/icassp55912.2026.11462635

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