Papers with hypernetwork-based approach
HYPEROFA: Expanding LLM Vocabulary to New Languages via Hypernetwork-Based Embedding Initialization (2025.acl-srw)
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| Challenge: | Pre-trained language models exhibit suboptimal performance on mid- and low-resource languages due to limited exposure to these languages during pre-training. |
| Approach: | They propose a similarity-based subword embedding initialization heuristic that introduces new tokens specific to target languages, initializes their embedders, and applies continual pre-training on target-language data. |
| Outcome: | The proposed method outperforms random initialization baseline and matches or exceeds OFA in both continual pre-training convergence and downstream task performance. |
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning (2023.eacl-main)
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| Challenge: | Recent advances apply artificial intelligence to predict clinical events or infer the probable diagnosis for clinical decision support. |
| Approach: | They propose a hypernetwork-based approach that generates task-conditioned parameters and coefficients of multitask prediction heads to learn task-specific prediction and balance the multitask learning. |
| Outcome: | Experiments on clinical notes from the real-world MIMIC database show that the proposed model can achieve better performance than baselines and improve zero-shot prediction on unseen diagnoses. |