Papers by Ya Gao
Beyond Surface Simplicity: Revealing Hidden Reasoning Attributes for Precise Commonsense Diagnosis (2025.acl-long)
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| Challenge: | Existing commonsense question answering benchmarks often treat these aspects in isolation, resulting in evaluation accuracy differences of up to 24.8% across different difficulty levels. |
| Approach: | They propose a framework that reveals hidden reasoning attributes behind commonsense questions by leveraging the knowledge generated during the reasoning process. |
| Outcome: | The proposed framework reveals hidden reasoning attributes behind commonsense questions by leveraging the knowledge generated during the reasoning process. |
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection (2024.lrec-main)
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| Challenge: | Recent studies have used word embedding and deep learning to automate ADE detection from text, but they did not incorporate explicit medical knowledge about drugs and adverse reactions or the corresponding feature learning. |
| Approach: | They propose to integrate medical knowledge into ADE detection from text . they use contextualized embeddings from pretrained language models and convolutional graph neural networks to learn features differently for different types of nodes in the graph. |
| Outcome: | The proposed model outperforms existing models on four public datasets and shows that it is based on medical knowledge and embeddings from pretrained language models and neural networks. |