Papers with unsupervised and supervised baselines
Seeded Hierarchical Clustering for Expert-Crafted Taxonomies (2022.findings-emnlp)
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| Challenge: | Practitioners from many disciplines use expert-crafted taxonomies to make sense of large, unlabeled corpora. |
| Approach: | They propose a weakly supervised algorithm for seeded hierarchical clustering that fits unlabeled data to taxonomies using a small set of labeled examples. |
| Outcome: | The proposed algorithm outperforms baselines on three real-world datasets. |
Fine-Grained Legal Argument-Pair Extraction via Coarse-Grained Pre-training (2024.lrec-main)
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| Challenge: | Current methods conceptualize LAE as a supervised sentence-pair classification problem and necessitate extensive manual annotations. |
| Approach: | They propose a model that focuses on fine-grained alignment of argument pairs building upon coarse-grain complaint-defense pairs. |
| Outcome: | The proposed model outperforms baseline models by 3.7 and 2.4 points on average. |