18 citations · 25 across the 6 of their papers we have counts for
6 papers
From Classification to Generation: Insights into Crosslingual Retrieval Augmented ICL
Xiaoqian Li, Ercong Nie, Sheng Liang
The remarkable ability of Large Language Models (LLMs) to understand and follow instructions has sometimes been limited by their in-context learning (ICL) performance in low-resour…
Crosslingual Retrieval Augmented In-context Learning for Bangla
Xiaoqian Li, Ercong Nie, Sheng Liang
The promise of Large Language Models (LLMs) in Natural Language Processing has often been overshadowed by their limited performance in low-resource languages such as Bangla. To add…
Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages
Ercong Nie, Sheng Liang, Helmut Schmid +1
Multilingual Pretrained Language Models (MPLMs) have shown their strong multilinguality in recent empirical cross-lingual transfer studies. In this paper, we propose the Prompts Au…
A review of knowledge graph application scenarios in cyber security
Kai Liu, Fei Wang, Zhaoyun Ding +3
Facing the dynamic complex cyber environments, internal and external cyber threat intelligence, and the increasing risk of cyber-attack, knowledge graphs show great application pot…
Modular and Parameter-Efficient Multimodal Fusion with Prompting
Sheng Liang, Mengjie Zhao, Hinrich Schütze
Recent research has made impressive progress in large-scale multimodal pre-training. In the context of the rapid growth of model size, it is necessary to seek efficient and flexibl…
Locating Language-Specific Information in Contextualized Embeddings
Sheng Liang, Philipp Dufter, Hinrich Schütze
Multilingual pretrained language models (MPLMs) exhibit multilinguality and are well suited for transfer across languages. Most MPLMs are trained in an unsupervised fashion and the…