A joint extraction framework that combines multi-branch dilated convolutions with a multi-head cross-attention mechanism together with a learnable gated fusion mechanism for feature interaction and adaptive fusion, thereby improving relation representation.
This article proposes a three-stage enhancement strategy: a global self-attention mechanism to enhance contextual modeling and boundary semantic representation; a dropout reorganization strategy to mitigate over-regularization during prediction; a dynamic gated fusion network to achieve adaptive aggregation of structur...
A novel multimodal entity alignment model- TextFusionEA is proposed, which implements structural embedding based on GraphSAGE, uses MobileNetV3 to obtain visual features, introduces an adaptive fusion mechanism of semantic, structural, and visual features, and designs a semi supervised iterative learning strategy to ex...
This work proposes Collaborative Entity Linking through Multichannel Interaction (CELMI), a four-channel framework that jointly models textual semantics, visual perception, cross-modal alignment, and inter-mention collaboration and introduces a multi-channel consistency objective that combines per-channel contrastive l...
Extensive experiments on three challenging fine-grained benchmarks demonstrate that MASFNet consistently outperforms state-of-the-art methods in both 5-way 1-shot and 5-way 5-shot settings.
Jinyu Wang, Bing-Xin Xu, Weiguo Pan et al.· International Conference on...· 0 citations
This study proposes STaR, a novel retriever fine-tuning framework that integrates BM25 similarity graph-based soft labeling with a triplet similarity learning strategy based on Sentence-BERT (SBERT), and introduces a triplet-aware SBERT training architecture that explicitly models relative semantic distances between qu...
Jiali Jiang, Chih-Yung Chang, Youxi Li et al.· Multimedia Systems· 0 citations
An Ambiguity-Aware Semantic Fusion Framework (AAK-LASFNet) for robust text classification and demonstrates that the proposed framework consistently outperforms strong baselines in terms of Accuracy, highlighting its effectiveness in alleviating semantic ambiguity in text classification.
Peijun Xie· Poster Volume 0007 The 2026...· 0 citations
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