On the Economics of Multilingual Few-shot Learning: Modeling the Cost-Performance Trade-offs of Machine Translated and Manual Data
Borrowing ideas from {\em Production functions} in micro-economics, in this paper we introduce a framework to systematically evaluate the performance and cost trade-offs between machine-translated and manually-created labelled data for task-specific fine-tuning of massively multilingual language models. We illustrate the effectiveness of our framework through a case-study on the TyDIQA-GoldP dataset. One of the interesting conclusions of the study is that if the cost of machine translation is greater than zero, the optimal performance at least cost is always achieved with at least some or only manually-created data. To our knowledge, this is the first attempt towards extending the concept of production functions to study data collection strategies for training multilingual models, and can serve as a valuable tool for other similar cost vs data trade-offs in NLP.
Code (0)
등록된 구현이 없습니다.
Tasks
Few-Shot LearningMachine TranslationTranslationSimilar Papers 제목 키워드 기반
Multilingual Speech Translation from Efficient Finetuning of Pretrained Models
We present a simple yet effective approach to build multilingual speech-to-text (ST) translation through efficient transfer learning from a pretrained speech encoder and text decoder. Our key finding is that a minimalist…
DecoderSpeech-to-TextText GenerationTransfer Learning+1Multilingual Speech Translation with Efficient Finetuning of Pretrained Models
We present a simple yet effective approach to build multilingual speech-to-text (ST) translation by efficient transfer learning from pretrained speech encoder and text decoder. Our key finding is that a minimalistic LNA …
Cross-Lingual TransferDecoderSpeech-to-TextText Generation+2Multilingual Definition Modeling
In this paper, we propose the first multilingual study on definition modeling. We use monolingual dictionary data for four new languages (Spanish, French, Portuguese, and German) and perform an in-depth empirical study t…
Adaptive Sparse Transformer for Multilingual Translation
Multilingual machine translation has attracted much attention recently due to its support of knowledge transfer among languages and the low cost of training and deployment compared with numerous bilingual models. A known…
Machine TranslationTransfer LearningTranslationxGQA: Cross-Lingual Visual Question Answering
Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer modeling efforts. In this work, we addres…
Cross-Lingual TransferLanguage ModelingLanguage ModellingQuestion Answering+3