Grounded Image Text Matching with Mismatched Relation Reasoning
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Abstract (arXiv)
This paper introduces Grounded Image Text Matching with Mismatched Relation (GITM-MR), a novel visual-linguistic joint task that evaluates the relation understanding capabilities of transformer-based pre-trained models. GITM-MR requires a model to first determine if an expression describes an image, then localize referred objects or ground the mismatched parts of the text. We provide a benchmark for evaluating pre-trained models on this task, with a focus on the challenging settings of limited data and out-of-distribution sentence lengths. Our evaluation demonstrates that pre-trained models lack data efficiency and length generalization ability. To address this, we propose the Relation-sensitive Correspondence Reasoning Network (RCRN), which incorporates relation-aware reasoning via bi-directional message propagation guided by language structure. RCRN can be interpreted as a modular program and delivers strong performance in both length generalization and data efficiency.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 55 of its 67 references that are in the map. First posted on arXiv 2 Aug 2023.
Builds on
55 of 67 references.
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Citing papers per year: 2024: 1; 2025: 6; 2026: 1.
8 papers.
- 2024FineCops-Ref: A new Dataset and Task for Fine-Grained Compositional Referring Expression Comprehensioncited by 20
- 2025Why LVLMs Are More Prone to Hallucinations in Longer Responses: The Role of Contextcited by 9
- 2025New Dataset and Methods for Fine-Grained Compositional Referring Expression Comprehension via Specialist-MLLM Collaborationcited by 7
- 2025Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formatscited by 6
- 2025Gradient-Attention Guided Dual-Masking Synergetic Framework for Robust Text-based Person Retrievalcited by 4
- 2025Language-Driven Object-Oriented Two-Stage Method for Scene Graph Anticipationcited by 1
- 2025EventRR: Event Referential Reasoning for Referring Video Object Segmentationcited by 0
- 2026DanQing: An Up-to-Date Large-Scale Chinese Vision-Language Pre-training Datasetcited by 0
- 2026DanQing: An Up-to-Date Large-Scale Chinese Vision-Language Pre-training Dataset15 Jan 2026
- 2025Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formats21 Nov 2025
- 2025Why LVLMs Are More Prone to Hallucinations in Longer Responses: The Role of Context23 Oct 2025
- 2025Gradient-Attention Guided Dual-Masking Synergetic Framework for Robust Text-based Person Retrieval11 Sep 2025
- 2025Language-Driven Object-Oriented Two-Stage Method for Scene Graph Anticipation6 Sep 2025
- 2025EventRR: Event Referential Reasoning for Referring Video Object Segmentation10 Aug 2025
- 2025New Dataset and Methods for Fine-Grained Compositional Referring Expression Comprehension via Specialist-MLLM Collaboration27 Feb 2025
- 2024FineCops-Ref: A new Dataset and Task for Fine-Grained Compositional Referring Expression Comprehension23 Sep 2024