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Found 5 papers, 3 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.
A Personalized Sentiment Model with Textual and Contextual Information
In this paper, we look beyond the traditional population-level sentiment modeling and consider the individuality in a person{'}s expressions by discovering both textual and contextual information.
