Interpreting ancient Chinese has been the key to comprehending vast Chinese literature,
tradition, and civilization. In this paper, we propose Erya for ancient Chinese translation …

Despite the rapid development of neural-based models, syntax still plays a crucial role in
modern natural language processing. However, few studies have incorporated syntactic …

To fully evaluate the overall performance of different NLP models in a given domain, many
evaluation benchmarks are proposed, such as GLUE, SuperGLUE and CLUE. The fi eld of …

While neural-based models continue to make rapid strides, syntax remains a foundational
element in the domain of Natural Language Processing (NLP), particularly in the context of …

Named entity recognition (NER) plays a crucial role in the extraction and utilization of
knowledge of ancient Chinese books. However, the challenges of ancient Chinese NER not …

Classical Chinese literature, with its long history spanning thousands of years, serves as an
invaluable resource for historical and humanistic studies. Previous classical Chinese …

The rapid development of generative artificial intelligence has brought significant
opportunities for the advancement of digital humanities research. Intelligent processing of …

The chapter focuses on the recent advancements in Artificial Intelligence (AI) and Machine
Learning (ML) applications within papyrological research. These technologies have a …

Text generation aims to produce human-like natural language output for down-stream tasks.
It covers a wide range of applications like machine translation, document summarization …

Automatic text dating (ATD) is a challenging task since explicit temporal mentions usually do
not appear in texts. Existing state-of-the-art approaches learn word representations via …