Generating domain-specific content such as legal clauses based on minimal user-provided information can be of significant benefit in automating legal contract generation. In this paper, we propose a controllable graph-based mechanism that can generate legal clauses using only the topic or type of the legal clauses. Our pipeline consists of two stages involving a graph-based planner followed by a clause generator. The planner outlines the content of a legal clause as a sequence of keywords in the order of generic to more specific clause information based on the input topic using a controllable graph-based mechanism. The generation stage takes in a given plan and generates a clause. The pipeline consists of a graph-based planner followed by text generation. We illustrate the effectiveness of our proposed two-stage approach on a broad set of clause topics in contracts.
Unsupervised Keyword Extraction from Polish Legal Texts
Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw（华沙大学跨学科数学与计算建模中心）；Faculty of Electronics and Information Technology, Warsaw University of Technology（华沙理工大学电子与信息技术学院）
Multi-Granularity Semantic Aware Graph Model for Reducing Position Bias in Emotion-Cause Pair Extraction
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）
Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features
Amsterdam Business School, University of Amsterdam（阿姆斯特丹大学阿姆斯特丹商学院）；European Patent Office（欧洲专利局）；Institute of Informatics, University of Amsterdam（阿姆斯特丹大学信息学院）
CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method
North China University of Technology（北方工业大学）；Beijing Key Laboratory of Key Technologies for AI+ Domain Applications（北京市AI+领域应用关键技术重点实验室）；Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data（大规模流数据集成与分析技术北京市重点实验室）
