“本文介绍了我们在第二十三届中文计算语言学大会中文抽象语义表示解析评测任务中提交的参赛系统。中文抽象语义表示(Chinese Abstract Meaning Representa-tion,CAMR)以一个单根可遍历的有向无环图表示中文句子的语义。本系统选择大语言模型作为解决方案。我们首先系统地评估了当下中文大语言模型在AMR解析任务上的性能,在此基础上基于图融合算法整合性能较高的大模型预测结果,最终得到预测的CAMR图。实验结果表明,1)现有大模型已经具备一定的少样本中文AMR解析能力;2)基于微调中文大模型的AMR解析系统能够取得相较以往最优系统更强的性能;3)图融合算法能够进一步增强基于大模型的CAMR解析系统的性能。”

“This paper introduces our systems submitted for the Chinese Vision-Language Understanding Evaluation task at the 23rd Chinese Computational Linguistics Conference.In this competition, we utilized X2-VLM and CCLM models to participate in various subtasks such as image-text retrieval, visual grounding, visual dialogue, and visual question answering. Additionally, we employed other models to assess performance on certain subtasks. We optimized our models and successfully applied them to these different tasks”