WebGithub Stars Date Published Github Stars. MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions ... Distinguish Confusing Law Articles for Legal Judgment Prediction. ... (LJP) is the task of automatically predicting a law case's judgment results given a text describing its facts, which has ... WebLegal Judgment Prediction (LJP) is the task of automatically predicting a law case’s judgment results given a text describing its facts, which has excellent prospects in …
Pinghui Wang Papers With Code
WebApr 1, 2024 · An end-to-end model, LADAN, is presented and a novel graph neural network, GDL, is proposed to automatically learn subtle differences between confusing law … WebDec 2, 2024 · An Element-aware Multi-representation Model for Law Article Prediction. Conference Paper. Full-text available. Jan 2024. Huilin Zhong. Junsheng Zhou. Weiguang Qu. Yanhui Gu. View. エテボース 対策 ポケカ
Similar Case Based Prison Term Prediction SpringerLink
WebLaw Articles Law Article 234: [The Crime of intentional injury] Whoever intentionally injures another person shall be sentenced to fixed-tenn imprisonment of not more than three years, criminal detention or public surveillance. " Charges Crime of intentional injury Terms of Penalty A fixed-term imprisonment of ten months WebDec 17, 2024 · 2.1 Legal Judgment Prediction. Legal Judgment Prediction is a fundamental task of legal intelligence, especially in civil law systems. Its subtasks in the context of criminal law generally contain law article prediction, charge prediction and prison term prediction [].Charge prediction often appears as the focus of research and is generally … WebIn this paper, we present an end-to-end model, LADAN, to solve the task of LJP. To distinguish confusing charges, we propose a novel graph neural network, GDL, to automatically learn subtle differences between confusing law articles, and also design a novel attention mechanism that fully exploits the learned differences to attentively … pannelli integrativi distanza