“This paper presents the work submitted for the 23rd China National Conference on Computational Linguistics(Evaluation Workshop)(CCL24-Eval), focusing on the Chinese Parataxis Graph (CPG) Parsing task. CPG represents Chinese natural language hierarchically through relational triplets, providing a consistent representation for linguistic units of varying levels. Our approach has used large-scale language models through full fine-tuning, achieving the result with F1 value at 71.6% in the contest and 74.76% after the contest. Furtehrmore, our team has proposed a combined model that integrates multiple LoRA fine-tuned medium-scale models after the contest. This approach is able to minimize the time and space consumption while keeping the performance of CPG construction task relatively high.”

“中文图文多模态理解评测任务旨在从多角度评价中文图文多模态预训练模型的图文多模态建模和理解能力。本任务共包括五个子任务:图片检索、文本检索、视觉问答、视觉定位和视觉对话,最终成绩根据这五个任务的得分综合计算。本文首先介绍了任务的背景和动机,然后从任务介绍、评价指标、比赛结果、参赛方法等方面介绍并展示了本次评测任务的相关信息。本次任务共有11支队伍报名参赛,其中3支队伍提交了结果。”