Papers with meta-learning baselines
Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection (2021.naacl-main)
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| Challenge: | Existing datasets for sarcasm detection are limited due to the difficulty in acquiring ground-truth annotations. |
| Approach: | They propose a generalized latent optimization strategy that allows different losses to accommodate each other and improves training dynamics. |
| Outcome: | The proposed approach outperforms transfer learning and meta-learning baselines and achieves 10.02% performance gain on the iSarcasm dataset. |
On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval (2023.findings-emnlp)
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| Challenge: | Visually-rich document entity retrieval (VDER) is an important topic in industrial NLP applications. |
| Approach: | They propose a task-aware meta-learning framework to tackle the problem of visually-rich document entity retrieval (VDER) they adopt a hierarchical decoder and employ contrastive learning to achieve this goal. |
| Outcome: | The proposed framework significantly improves the robustness of popular meta-learning baselines. |