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WIDE: Wildcard Inference with Dynamic Expansion for Cross-Modal Generative Retrieval

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation task. However, extending this paradigm to cross-modal retrieval reveals a critical challenge arising from the inherent information asymmetry across different modalities, such as the gap between concise text queries and dense visual candidates. This structural mismatch causes the autoregressive decoder to suffer from forced hallucination when generating identifiers via standard trie-constrained beam search, where the model is severely penalized f

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