Papers with zero-shot cross-lingual tasks
Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels (2022.findings-naacl)
Copied to clipboard
| Challenge: | Existing methods to train pre-trained language models for zero-shot cross-lingual tasks are noisy and lack confidence. |
| Approach: | They propose an uncertainty-aware cross-lingual transfer framework with pseudo-partial-label to maximize the utilization of unlabeled data by reducing noise. |
| Outcome: | The proposed framework outperforms baselines on named entity recognition and natural language inference tasks on 40 languages. |
Toward the Limitation of Code-Switching in Cross-Lingual Transfer (2022.emnlp-main)
Copied to clipboard
| Challenge: | Recent studies have shown the success of multilingual pretrained models for cross-lingual knowledge transfer. |
| Approach: | They propose to make code-switched sentences replace tokens from multiple languages so they are grammatically consistent . they also consider the similarity between context and the switched tokens to ensure that the newly substituted sentences are grammatically consistent - a limitation that could affect inference . |
| Outcome: | The proposed method outperforms the mBERT and original code-switching method on cross-lingual POS and Named-Entity-Recognition tasks on 30+ languages. |