Question answering (QA) and Machine Reading Comprehension (MRC) tasks have
significantly advanced in recent years due to the rapid development of deep learning …

The efficacy of large-scale language models (LLMs) as few-shot learners has dominated the
field of natural language processing, achieving state-of-the-art performance in most tasks …

In the rapidly evolving field of sports analytics, the automation of targeted video processing
is a pivotal advancement. We propose PlayerTV, an innovative framework which harnesses …

In this paper, we address the detection of named entities in multilingual historical collections.
We argue that, besides the multiple challenges that depend on the quality of digitization (eg …

This paper focuses on Information Extraction from Visually Rich Documents, exploring how
deep learning methods are applied in this field. For the purpose of comparing the …

Triplet extraction is the key technology to automatically construct knowledge graphs.
Extracting the triplet of mechanical equipment fault relationships is of great significance in …

Abstract Optical Character Recognition (OCR) continues to face accuracy challenges that
impact subsequent applications. To address these errors, we explore the utility of OCR …

Abstract Optical Character Recognition (OCR) plays a pivotal role in enhancing the
operational efficiency of container ports. However, challenges such as angle limitations and …

Text role classification involves classifying the semantic role of textual elements within
scientific charts. We propose to finetune the multimodal document layout analysis models …

The lack of generalizability--in which a model trained on one dataset cannot provide
accurate results for a different dataset--is a known problem in the field of document layout …