The rapid development of Large Language Models (LLMs) demonstrates remarkable
multilingual capabilities in natural language processing, attracting global attention in both …

Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

This study explored the potential of manual augmentation in enhancing the comprehension
and translation capabilities of large language models, specifically focusing on the LLaMA …

Recent mainstream event argument extraction methods process each event in isolation,
resulting in inefficient inference and ignoring the correlations among multiple events. To …

Multilingual large language models (MLLMs) leverage advanced large language models to
process and respond to queries across multiple languages, achieving significant success in …

Semi-supervised learning (SSL) is a widely used technique in scenarios where labeled data
is scarce and unlabeled data is abundant. While SSL is popular for image and text …

In NLG meta-evaluation, evaluation metrics are typically assessed based on their
consistency with humans. However, we identify some limitations in traditional NLG meta …

Despite being heralded as the new standard for dialogue evaluation, the closed-source
nature of GPT-4 poses challenges for the community. Motivated by the need for lightweight …

Recent advances in natural language processing (NLP), particularly in the subspace of
large language modeling, have led to a major paradigm shift. Large language models …