Cross-Lingual Semantic Role Labeling with High-Quality Translated Training Corpus

Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding. Supervised approaches have achieved impressing performances when large-scale corpora are available for resource-rich languages such as English. While for the low-resource languages with no annotated SRL dataset, it is still challenging to obtain competitive performances. Cross-lingual SRL is one promising way to address the problem, which has achieved great advances with the help of model transferring and annotation projection. In this paper, we propose a novel alternative based on corpus translation, constructing high-quality training datasets for the target languages from the source gold-standard SRL annotations. Experimental results on Universal Proposition Bank show that the translation-based method is highly effective, and the automatic pseudo datasets can improve the target-language SRL performances significantly.Comment: Accepted at ACL 202

Polyethylenimine-Modified Multiwalled Carbon Nanotubes for Plasmid DNA Gene Delivery

An efficient molecular delivery technique based on the transporting high-molecular-weight PEI 600K-modified multiwalled carbon nanotubes (PEI 600K-MWCNTs) into cell membranes is reported. The PEI 600K-MWCNTs exhibit low cytotoxicity and its associated plasmid DNA (pDNA) is delivered to cells efficiently, and the green fluorescent protein (GFP) levels up to 18 times higher than that of naked DNA were observed