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Found 5 papers, 4 papers with code
Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to Luxembourgish
A common method for ZSC is to fine-tune a language model on a Natural Language Inference (NLI) dataset and then use it to infer the entailment between the input document and the target labels.
Soft Prompt Tuning for Cross-Lingual Transfer: When Less is More
Soft Prompt Tuning (SPT) is a parameter-efficient method for adapting pre-trained language models (PLMs) to specific tasks by inserting learnable embeddings, or soft prompts, at the input layer of the PLM, without modifying its parameters.
Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Review
To enhance the structure of this review and to facilitate consolidation with future studies, we identify five categories of such factors.
Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space
Prior research has investigated the impact of various linguistic features on cross-lingual transfer performance.
Yes, we can! Mining Arguments in 50 Years of US Presidential Campaign Debates
We address this task in an empirical manner by annotating 39 political debates from the last 50 years of US presidential campaigns, creating a new corpus of 29k argument components, labeled as premises and claims.
