Papers by Guangli Li

2 papers
DDGIP: Radiology Report Generation Through Disease Description Graph and Informed Prompting (2025.findings-naacl)

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Challenge: Automatic radiology report generation is challenging due to inherent biases in medical imaging data.
Approach: They propose a disease description graph that encapsulates comprehensive and pertinent disease information.
Outcome: The proposed model outperforms state-of-the-art models on two widely-used datasets . the proposed model is based on a three-layer decoder and improves on existing models .
ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models (2025.coling-main)

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Challenge: Activation sparsity is a promising paradigm for accelerating model inference . few large language models achieve high activation spar and comparable performance .
Approach: They propose a method to achieve activation sparsity and acceleration in large language models . they introduce ReLU activation and adopt progressive sparse regularization .
Outcome: The proposed method achieves high activation sparsity and comparable model performance.

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