5 accepted papers
Deep generative models have advanced text-to-online handwriting generation (TOHG), which aims to synthesize realistic pen trajectories conditioned on textual input and style references. However, most existing methods still primarily focus on character- or word-level generation, resulting in ineffici…
Ancient Chinese Poetry (ACP), a critical aspect of Chinese cultural heritage, presents unique challenges for Large Language Models (LLMs). One of the most pressing challenges is the significant hallucination issues faced by LLMs due to data scarcity and limited ability of general LLMs when dealing w…
With the rapid development of Multimodal Large Language Models (MLLMs), their potential in Chinese Classical Studies (CCS), a field which plays a vital role in preserving and promoting China’s rich cultural heritage, remains largely unexplored due to the absence of specialized benchmarks. To bridge…
Document layout analysis is a crucial step for intelligent document understanding. However, many existing methods primarily focus on the visual aspects and overlook the textual features of documents. Although document pre-trained models utilize multi-modal features during the pre-training phase, the…
Document layout analysis is a crucial prerequisite for document understanding, including document retrieval and conversion. Most public datasets currently contain only PDF documents and lack realistic documents. Models trained on these datasets may not generalize well to real-world scenarios. Theref…