Papers with statistical modeling
Few-shot Classification with Hypersphere Modeling of Prototypes (2023.findings-acl)
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| Challenge: | Existing methods for fewshot learning use embeddings in space, but they lack expressivity and are difficult to perform statistically. |
| Approach: | They propose a method where class information is represented by hyperspheres with dynamic sizes with two sets of learnable parameters: the hypersphere’s center and the radius. |
| Outcome: | The proposed method is much more expressive than embeddings and performs better than statistical modeling. |
Text2Tabular – Reconstructing Tabular Research Data from Scientific Publications (2026.acl-long)
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| Challenge: | Text2Tabular reconstructs research datasets from scientific literature using advanced natural language processing and statistical modeling. |
| Approach: | Text2Tabular reconstructs research datasets from scientific publications using natural language processing and statistical modeling. |
| Outcome: | Text2Tabular reconstructs scientific literature-based datasets using natural language processing and statistical modeling. |
Improving Textual Network Embedding with Global Attention via Optimal Transport (P19-1)
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Liqun Chen, Guoyin Wang, Chenyang Tao, Dinghan Shen, Pengyu Cheng, Xinyuan Zhang, Wenlin Wang, Yizhe Zhang, Lawrence Carin
| Challenge: | Existing methods for learning textual network embeddings are noisy and sparse. |
| Approach: | They propose to use text-based attention parsing to learn context-aware network embeddings. |
| Outcome: | The proposed model outperforms state-of-the-art methods in a number of domains. |