IN2R rectifies inter-modal noisy correspondence by synthesizing continuous soft prototypes from intra-modal neighbor consensus using a Graph Refiner on dynamic cross-modal memory.
Unimo: Towards unified-modal un- derstanding and generation via cross-modal contrastive learning
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Gaze2Report combines predicted eye-gaze scanpaths and graph neural networks with LoRA-tuned LLMs to generate radiology reports that incorporate human visual attention without requiring gaze data at inference time.
citing papers explorer
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Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning
IN2R rectifies inter-modal noisy correspondence by synthesizing continuous soft prototypes from intra-modal neighbor consensus using a Graph Refiner on dynamic cross-modal memory.
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Gaze2Report: Radiology Report Generation via Visual-Gaze Prompt Tuning of LLMs
Gaze2Report combines predicted eye-gaze scanpaths and graph neural networks with LoRA-tuned LLMs to generate radiology reports that incorporate human visual attention without requiring gaze data at inference time.