A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters (2021.acl-long)
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| Challenge: | Few-shot crosslingual transfer outperforms zero-shot with pretrained encoders like multilingual BERT. |
| Approach: | They conduct an experimental study on 40 sets of sampled few shots for six diverse NLP tasks across up to 40 languages. |
| Outcome: | The proposed model outperforms state-of-the-art approaches on lexical features and a full model finetuning approach outperformed several state- of-the art approaches. |
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| Challenge: | Recent studies have focused on zero-shot cross-lingual transfer of pretrained languages. |
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Zero- and Few-Shot NLP with Pretrained Language Models (2022.acl-tutorials)
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| Challenge: | a tutorial aims to introduce NLP researchers to the latest techniques for learning from little-to-no data . aims at bringing interested researchers up to speed about the latest and ongoing techniques . |
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Few-shot Learning with Multilingual Generative Language Models (2022.emnlp-main)
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Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O’Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona Diab, Veselin Stoyanov, Xian Li
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Massively Multilingual Transfer for NER (P19-1)
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| Challenge: | Existing approaches for cross-lingual transfer use a single source language, but there are exceptions. |
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Making Pre-trained Language Models Better Few-shot Learners (2021.acl-long)
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| Challenge: | Recent studies show that the GPT-3 model can perform few-shots on language understanding tasks with a natural-language prompt and a few task demonstrations. |
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BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer (2024.naacl-long)
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Akari Asai, Sneha Kudugunta, Xinyan Yu, Terra Blevins, Hila Gonen, Machel Reid, Yulia Tsvetkov, Sebastian Ruder, Hannaneh Hajishirzi
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Why Does Zero-Shot Cross-Lingual Generation Fail? An Explanation and a Solution (2023.findings-acl)
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| Challenge: | Existing studies on cross-lingual transferability of multilingual LMs show that they can perform tasks in low-resource languages. |
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Nearest Neighbour Few-Shot Learning for Cross-lingual Classification (2021.emnlp-main)
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| Challenge: | Existing pre-trained models can cause over-fitting when limited data are available. |
| Approach: | They propose to use a nearest-neighbor few-shot technique to improve cross-lingual adaptation using 16 distinct languages across two NLP tasks. |
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Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks (2024.naacl-long)
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| Challenge: | Existing studies have focused on zero-shot cross-lingual transfer . mBERT, mBART and mT5 provide high-quality representations for texts in various languages . |
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