Papers by Haiyan Ning
VAEGPT-Sim: Improving Sentence Representation with Limited Corpus Using Gradually-Denoising VAE (2024.findings-acl)
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| Challenge: | Text embedding requires a highly efficient method for training domain-specific models on limited corpora. |
| Approach: | They propose a model that combines a denoising variational autoencoder with a target-specific discriminator to generate synonymous sentences that closely resemble human language. |
| Outcome: | The proposed model surpasses ConSERT by 2.8 points in small-dataset training on STS benchmarks. |
HMCL: Task-Optimal Text Representation Adaptation through Hierarchical Contrastive Learning (2025.findings-emnlp)
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| Challenge: | Hierarchical Multilevel Contrastive Learning (HMCL) improves text representation for general large language models. |
| Approach: | a new contrastive learning framework is developed to improve general large language models . HMCL integrates 3-level semantic differentiation and unifies contrastive and pair classification into a strategy . |
| Outcome: | HMCL outperforms unsupervised methods and supervised fine-tuning approaches in multi-domain and multilingual benchmarks. |