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A Keyword-Guided Training Approach to Large Language Models for Judicial Document Generation
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作者 Yi-Ting Peng Chin-Laung Lei 《Computer Modeling in Engineering & Sciences》 2025年第12期3969-3992,共24页
The rapid advancement of Large Language Models(LLMs)has enabled their application in diverse professional domains,including law.However,research on automatic judicial document generation remains limited,particularly f... The rapid advancement of Large Language Models(LLMs)has enabled their application in diverse professional domains,including law.However,research on automatic judicial document generation remains limited,particularly for taiwan region of China courts.This study proposes a keyword-guided training framework that enhances LLMs’ability to generate structured and semantically coherent judicial decisions in Chinese.The proposed method first employs LLMs to extract representative legal keywords from absolute court judgments.Then it integrates these keywords into Supervised Fine-Tuning(SFT)and Reinforcement Learning withHuman Feedback using Proximal Policy Optimization(RLHF-PPO).Experimental evaluations using models such as Chinese Alpaca 7B and TAIDE-LX-7B demonstrate that keyword-guided training significantly improves generation quality,achieving ROUGE-1,ROUGE-2,and ROUGE-L score gains of up to 17%,16%,and 20%,respectively.The results confirm that the proposed framework effectively aligns generated judgments with human-written legal logic and structural conventions.This research advances domainadaptive LLM fine-tuning strategies and establishes a technical foundation forAI-assisted judicial document generation in the taiwan region of China legal context.This research provides empirical evidence that domain-adaptive LLM fine-tuning strategies can significantly improve performance in complex,structured legal text generation. 展开更多
关键词 Legal AI large languagemodels natural language processing generative AI legal document generation
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Resolution Characteristics of GaAs/GaAlAs Transmission Photocathode
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作者 YAN Jin-liang,ZHAO Yin-nu,ZHU Chang-chun (School of Electron. & Inform.Eng.,Xi’an Jiaotong University,Xi’an 710049,CHN) 《Semiconductor Photonics and Technology》 CAS 1999年第2期96-100,共5页
The resolution characteristic of GaAs/GaAlAs transmission photocathode is an important parameter in third generation intensifiers. The modulation transfer function of GaAs/GaAlAs transmission photo... The resolution characteristic of GaAs/GaAlAs transmission photocathode is an important parameter in third generation intensifiers. The modulation transfer function of GaAs/GaAlAs transmission photocathode is derived from a simple two-dimensional diffusion equation. The theoretical resolution characteristic of a 2 μm thick GaAs/GaAlAs transmission photocathode is calculated. The relationship between resolution and parameters in GaAs/GaAlAs transmission photocathode is discussed. A conclusion is shown that one can design the GaAs/GaAlAs transmission photocathode for maximum quantum efficiency, since the sacrifice in the resolution doesn't limit system performances. 展开更多
关键词 GaAs/GaAlAs Photocathode Quantum Yield RESOLUTION Third generation Intensifier CLC number:TN383.4 document code:A
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