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Found 5 papers, 4 papers with code
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
We find that even though translation into English can help improve the performance of multilingual NLP tasks for English-centric LLMs, it may not be optimal for all scenarios.
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
Hierarchical topic modeling aims to discover latent topics from a corpus and organize them into a hierarchy to understand documents with desirable semantic granularity.
SeaLLMs -- Large Language Models for Southeast Asia
Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at the expense of low-resource and regional languages.
Zero-Shot Text Classification via Self-Supervised Tuning
In this work, we propose a new paradigm based on self-supervised learning to solve zero-shot text classification tasks by tuning the language models with unlabeled data, called self-supervised tuning.
InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modeling
Instead of the direct alignment in previous work, we propose a topic alignment with mutual information method.
