Papers with positive knowledge transfer
Continual Few-shot Intent Detection (2022.coling-1)
Copied to clipboard
| Challenge: | Existing intent detection systems are trained with lots of labeled data over a predefined set of intent classes. |
| Approach: | They propose a prefix-guided lightweight encoder with three auxiliary strategies to prevent catastrophic forgetting and negative knowledge transfer across tasks. |
| Outcome: | The proposed system prevents catastrophic forgetting and encourages positive knowledge transfer across tasks. |
Multitask Learning for Emotionally Analyzing Sexual Abuse Disclosures (2021.naacl-main)
Copied to clipboard
| Challenge: | Prior work on identifying narratives related to sexual abuse disclosures did not consider this as an independent task. |
| Approach: | They propose to identify narratives related to sexual abuse disclosures as a joint modeling task that leverages their emotional attributes through multitask learning. |
| Outcome: | The proposed model leverages emotional attributes of textual conversations to identify narratives related to sexual abuse disclosures in homogeneous and heterogeneously settings. |
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering (2022.coling-1)
Copied to clipboard
| Challenge: | Existing clustering methods cannot handle asymmetric problem in multilingual NMT . existing models cannot handle the asymmetry problem since there are thousands of languages involved . |
| Approach: | They propose a fuzzy task clustering method to address the asymmetric problem in multilingual NMT by using task affinity as the clustering criterion. |
| Outcome: | The proposed method outperforms baselines for a multilingual model and the existing models. |
Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation (2023.emnlp-main)
Copied to clipboard
| Challenge: | Using a shared vocabulary is common practice in multilingual machine translation . however, when words overlap is small, e.g., using different writing systems, knowledge transfer is inhibited . |
| Approach: | They propose a re-parameterized method for building word embeddings using word equivalence classes and graph networks to fuse word embeds across languages. |
| Outcome: | The proposed method achieves evident BLEU improvements on high- and low-resource MNMT scenarios. |