Related papers: Some Chances and Challenges in Applying Language T…

We analyzed historical and literary documents in Chinese to gain insights into research issues, and overview our studies which utilized four different sources of text materials in this paper. We investigated the history of concepts and…

Ancient Chinese texts present an area of enormous challenge and opportunity for humanities scholars interested in exploiting computational methods to assist in the development of new insights and interpretations of culturally significant…

This paper proposes HistoLens, a multi-layered analysis framework for historical texts based on Large Language Models (LLMs). Using the important Western Han dynasty text "Yantie Lun" as a case study, we demonstrate the framework's…

Temporal reasoning is fundamental to human cognition and is crucial for various real-world applications. While recent advances in Large Language Models have demonstrated promising capabilities in temporal reasoning, existing benchmarks…

While Large Language Models (LLMs) have demonstrated advanced reasoning capabilities, their comprehensive evaluation in general Chinese-language contexts remains understudied. To bridge this gap, we propose Chinese Commonsense Multi-hop…

This paper presents a quantitative approach to studying linguistic and cultural change in China during the first half of the twentieth century, a period that remains understudied in computational humanities research. The dramatic changes in…

Chinese dynastic histories form a large continuous linguistic space of approximately 2000 years, from the 3rd century BCE to the 18th century CE. The histories are documented in Classical (Literary) Chinese in a corpus of over 20 million…

We consider three major text sources about the Tang Dynasty of China in our experiments that aim to segment text written in classical Chinese. These corpora include a collection of Tang Tomb Biographies, the New Tang Book, and the Old Tang…

This paper compares large language models (LLMs) and traditional natural language processing (NLP) tools for performing word segmentation, part-of-speech (POS) tagging, and named entity recognition (NER) on Chinese texts from 1900 to 1950.…

In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese. Humans have produced texts in various languages for thousands of years; however, most of the computational literature is focused on…

We propose a Historical Document Reading Challenge on Large Chinese Structured Family Records, in short ICDAR2019 HDRC CHINESE. The objective of the proposed competition is to recognize and analyze the layout, and finally detect and…

Accessibility to historical documents is mostly limited to scholars. This is due to the language barrier inherent in human language and the linguistic properties of these documents. Given a historical document, modernization aims to…

The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the…

Constructing historical language models (LMs) plays a crucial role in aiding archaeological provenance studies and understanding ancient cultures. However, existing resources present major challenges for training effective LMs on historical…

This paper proposes a framework for evaluating large language models (LLMs) on Chinese topic constructions, focusing on their sensitivity to island constraints. Drawing inspiration from Tian et al. (2024), we outline an experimental design…

Tomb biographies of the Tang dynasty provide invaluable information about Chinese history. The original biographies are classical Chinese texts which contain neither word boundaries nor sentence boundaries. Relying on three published books…

While Large Language Models (LLMs) have increasingly assisted in historical tasks such as text processing, their capacity for professional-level historical reasoning remains underexplored. Existing benchmarks primarily assess basic…

The birth and rapid development of large language models (LLMs) have caused quite a stir in the field of literature. Once considered unattainable, AI's role in literary creation is increasingly becoming a reality. In genres such as poetry,…

Large language models often struggle with complex long-horizon analytical tasks over unstructured tables, which typically feature hierarchical and bidirectional headers and non-canonical layouts. We formalize this challenge as Deep Tabular…

While large language models (LLMs) have achieved remarkable success in general language tasks, their performance on Chouxiang Language, a representative subcultural language in the Chinese internet context, remains largely unexplored. In…