Psycholinguistic Tripartite Graph Network for Personality Detection (2021.acl-long)
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| Challenge: | Existing work on personality detection from online posts adopts multifarious deep neural networks to represent the posts and builds predictive models in a data-driven manner without the exploitation of psycholinguistic knowledge. |
| Approach: | They propose a psycholinguistic knowledge-based tripartite graph network, TrigNet, which consists of a tripartitic graph network and a BERT-based graph initializer. |
| Outcome: | The proposed graph network outperforms the existing state-of-the-art model by 3.47 and 2.10 points in average F1 on two datasets. |
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Lingua-Graph: A Unified Representation of Cross-Task Common Substructures for Analytic Language Processing (2026.acl-long)
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| Challenge: | Existing structural-analytic tasks are fragmented by inconsistent task requirements . we propose a solution for the representation layer, called Lingua-Graph . |
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AnyGraph: Graph Foundation Model in the Wild (2026.findings-acl)
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| Challenge: | Existing graph learning models struggle to extract generalizable insights from heterogeneous graph data, requiring extensive fine-tuning and limiting versatility across domains. |
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A structure-enhanced graph convolutional network for sentiment analysis (2020.findings-emnlp)
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Self-attention-based Graph-of-Thought for Math Problem Solving (2025.findings-acl)
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