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   Articles with "graph reasoning" as a keyword



A contrastive learning framework with dual gates and noise awareness for temporal knowledge graph reasoning

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-00314-w

Abstract: Temporal knowledge graph reasoning(TKGR) has attracted widespread attention due to its ability to handle dynamic temporal features. However, existing methods face three major challenges: (1) the difficulty of capturing long-distance dependencies in information sparse environments;… read more here.

Keywords: graph reasoning; framework; contrastive learning; temporal knowledge ... See more keywords

HieraASGSegNet: Hierarchical Context Fusion for Semantic Segmentation via Adaptive Superpixel Graph Reasoning

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3626744

Abstract: Semantic segmentation remains challenging in real-world scenes due to variations in object scale, frequent occlusions, and ambiguous boundaries. We propose HieraASGSegNet, a hierarchical segmentation framework that performs adaptive superpixel graph reasoning. In this framework, each… read more here.

Keywords: graph reasoning; superpixel graph; segmentation; semantic segmentation ... See more keywords

Efficient Cross-Modality Graph Reasoning for RGB-Infrared Person Re-Identification

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recommendations! Published in 2021 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2021.3093865

Abstract: The modality and pose variance between RGB and infrared (IR) images are two key challenges for RGB-IR person re-identification. Existing methods mainly focus on leveraging pixel or feature alignment to handle the intra-class variations and… read more here.

Keywords: modality; graph reasoning; cross modality; identification ... See more keywords

Dual Graph Inference Network for Weakly Supervised Semantic Segmentation

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2025.3544331

Abstract: Establishing global contextual relationships between objects is crucial for weakly supervised semantic segmentation (WSSS) tasks that lack pixel-level labels. Limited by the efficiency of convolutional operations in capturing long-range dependencies with a limited receptive field… read more here.

Keywords: graph reasoning; weakly supervised; dual graph; semantic segmentation ... See more keywords

Dual Graph Reasoning Network for Oil Leakage Segmentation in Substation Equipment

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recommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2023.3336439

Abstract: Oil leakage inspection is critical to ensure the safety of substation operations. However, weak edges and irregular segmentation pose challenges in oil leakage inspection tasks. To address these challenges, this article proposes a semantic segmentation… read more here.

Keywords: segmentation; graph reasoning; oil leakage; oil ... See more keywords

Multi-Hop Knowledge Graph Reasoning in Few-Shot Scenarios

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recommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2023.3304665

Abstract: Reinforcement learning (RL)-based multi-hop reasoning has become an interpretable way for knowledge graph reasoning owing to its persuasive explanations for the predicted results, but the reasoning performance of these methods drops significantly over few-shot relations… read more here.

Keywords: knowledge; graph reasoning; multi hop; knowledge graph ... See more keywords

Progressive Graph Reasoning-Based Social Relation Recognition

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recommendations! Published in 2024 at "IEEE Transactions on Multimedia"

DOI: 10.1109/tmm.2023.3344359

Abstract: Identifying relationships between people from images is essential for studying social activities and interactions, and this has significant potential to further the understanding of human social behaviors. Existing image-based research mainly explores social relationships at… read more here.

Keywords: relation; graph reasoning; progressive graph; recognition ... See more keywords

Graph Reasoning With Supervised Contrastive Learning for Legal Judgment Prediction

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recommendations! Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2023.3344634

Abstract: Given the fact descriptions of legal cases, the legal judgment prediction (LJP) problem aims to determine three judgment tasks of law articles, charges, and the term of penalty. Most existing studies have considered task dependencies… read more here.

Keywords: graph reasoning; legal judgment; judgment prediction; contrastive learning ... See more keywords

Compressing Transfer: Mutual Learning- Empowered Knowledge Distillation for Temporal Knowledge Graph Reasoning

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recommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2025.3525699

Abstract: With the widespread application of temporal knowledge graph reasoning (TKGR) models, there is an increasing demand to reduce the memory consumption and enhance the reasoning efficiency. Knowledge distillation (KD) is a classical approach to achieve… read more here.

Keywords: knowledge; graph reasoning; knowledge distillation; transfer ... See more keywords
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Instance-Level Relative Saliency Ranking with Graph Reasoning

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recommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.1109/tpami.2021.3107872

Abstract: Conventional salient object detection models cannot differentiate the importance of different salient objects. Two works have proposed to detect saliency ranking by assigning different degrees of saliency to different objects. However, one of these models… read more here.

Keywords: graph reasoning; instance; saliency ranking; relative saliency ... See more keywords

Agentic deep graph reasoning yields self-organizing knowledge networks

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recommendations! Published in 2025 at "Journal of Materials Research"

DOI: 10.1557/s43578-025-01652-1

Abstract: We present an agentic, autonomous graph expansion framework that iteratively structures and refines knowledge in situ. Unlike conventional knowledge graph construction methods relying on static extraction or single-pass learning, our approach couples a reasoning-native large… read more here.

Keywords: deep graph; knowledge; graph reasoning; reasoning yields ... See more keywords