Papers with multi-task learning techniques
PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from related Example Banks (2025.naacl-long)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have demonstrated impressive few-shot learning capabilities through in-context learning. |
| Approach: | They propose a novel Alternating Minimization approach for example selection that improves ICL performance on low-resource Indic languages. |
| Outcome: | The proposed approach outperforms existing frameworks for retrieving examples on low-resource Indic languages. |
Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods to solve the extraction problem learn interactions between the two tasks through a shared network . |
| Approach: | They propose to use multi-task learning to address the joint extraction of entity and relation . they exploit correlation between ER and relation classification tasks to improve performance . |
| Outcome: | Empirical results show that the proposed model improves on two real-world datasets. |