Titlebook: Natural Language Processing and Chinese Computing; 13th National CCF Co Derek F. Wong,Zhongyu Wei,Muyun Yang Conference proceedings 2025 Th

Ganglion

Hang Jiang,Guoyong Cai,Sihui Liins with a concluding summary of the main findings in delivering the representational, the compositional and the interactive meanings in subtitling. Then, it moves on to the discussion of these findings by referring to relevant previous studies and the theoretical framework employed in this book. In

Aboveboard

Yang Jiang,Jun Chen,Kai Han,Yi Liu,Siqi Ma,Yuqing Song,Zhe Liu practitioner lawyers and scholars. However this patchworking process has rarely taken place with attention to methodology, rather it has been arbitrary, depending upon which participants are most influential in a given forum, and what their preference is for specific domestic systems of liability.

涂掉

Pengfei Wu,Jiahao Liu,Zhuocheng Gong,Qifan Wang,Jinpeng Li,Jingang Wang,Xunliang Cai,Dongyan Zhaotates as the predominant law-makers, and considers domestic case law to be merely a subsidiary source of law. This is a static view of the law, which does not take into account the actual processes by which certain branches of international law are formed. A more dynamic view is therefore proposed i

chisel

Yuan Wutates as the predominant law-makers, and considers domestic case law to be merely a subsidiary source of law. This is a static view of the law, which does not take into account the actual processes by which certain branches of international law are formed. A more dynamic view is therefore proposed i

搖擺

Qiuyu Liang,Weihua Wang,Jie Yu,Feilong Baoair towards defendants. Two sets of tensions created by these demands are discussed in this chapter. The first is the tension between efficacy and symbolism; the desire for an efficient system of prosecutions requires a clarity of goals, yet there are numerous and competing goals asserted by those w

不給啤

carotid-bruit

Improving Causal Inference of?Large Language Models with?SCM Toolscent study showed the poor ability of LLMs to perform causal inference based on causal graphs and data. In this paper, we propose a method to enhance LLMs based on Structure Causal Model (SCM) tools. We constructed 10 causal inference tools based on SCM theory for solving 10 different types of causa

伴隨而來

前奏曲

Measured

LasQ: Largest Singular Components Fine-Tuning for?LLMs with?Quantization of fine-tuning the entire model becomes extremely high. To address this challenge, we focus on applying quantization and LoRA fine-tuning together in pre-training scenarios and propose an efficient parameter fine-tuning (PEFT) method, the LasQ (Largest Singular Components Fine-tuning for LLMs with