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[2509.24072] Uncovering Grounding IDs: How External Cues Shape Multimodal Binding
Summary
This article explores the concept of Grounding IDs, which are latent identifiers that enhance multimodal binding in large vision-language models (LVLMs) by leveraging external cues.
Why It Matters
Understanding how Grounding IDs function can significantly improve the performance of LVLMs in tasks requiring structured reasoning and precise grounding. This research offers insights into enhancing cross-modal interactions, which is crucial for applications in AI and computer vision.
Key Takeaways
- Grounding IDs are latent identifiers that improve object binding across modalities.
- External visual structures enhance the accuracy of LVLMs by reducing modality gaps.
- Causal interventions confirm that Grounding IDs mediate the binding process between objects and symbolic cues.
- Strengthening attention between related components leads to better cross-modal grounding.
- The findings provide both interpretability and practical improvements for multimodal AI applications.
Computer Science > Computer Vision and Pattern Recognition arXiv:2509.24072 (cs) [Submitted on 28 Sep 2025 (v1), last revised 25 Feb 2026 (this version, v4)] Title:Uncovering Grounding IDs: How External Cues Shape Multimodal Binding Authors:Hosein Hasani, Amirmohammad Izadi, Fatemeh Askari, Mobin Bagherian, Sadegh Mohammadian, Mohammad Izadi, Mahdieh Soleymani Baghshah View a PDF of the paper titled Uncovering Grounding IDs: How External Cues Shape Multimodal Binding, by Hosein Hasani and 6 other authors View PDF HTML (experimental) Abstract:Large vision-language models (LVLMs) show strong performance across multimodal benchmarks but remain limited in structured reasoning and precise grounding. Recent work has demonstrated that adding simple visual structures, such as partitions and annotations, improves accuracy, yet the internal mechanisms underlying these gains remain unclear. We investigate this phenomenon and propose the concept of Grounding IDs, latent identifiers induced by external cues that bind objects to their designated partitions across modalities. Through representation analysis, we find that these identifiers emerge as consistent within-partition alignment in embedding space and reduce the modality gap between image and text. Causal interventions further confirm that these identifiers mediate binding between objects and symbolic cues. We show that Grounding IDs strengthen attention between related components, which in turn improves cross-modal grounding and ...
