The Language Model for Legal Retrieval and Bert-based Model for Rhetorical Role Labeling for Legal Judgments

From this inspection, the experts recorded whether there is a semantic correspondence of these words concerning the main thematic of each legal document analyzed (comparing them

We argue that whereas the proposed definition of AI system is broad, the concrete high-risk area of ‘administration of justice and democratic processes’, despite

In this proposed work explains the method used to solve the problem given in the shared task on Artificial Intelligence for Legal Assistance proposed by the Forum of

Different learning rate, epoch , and random seed are tested.When it come to the train data, we randomly chose 80% of the given documents and use them as the train data,10% of

Also [4], proposing a similar approach, wherein BM25 was used to compute the similarity between the case documents and queries and BERT [5] being the component to map the

A transformer-based language model (RoBERTa) pretrained over an extensive English language corpus and fine-tuned on legal judgments from the Supreme Court is presented along with

Motivated by the above scenario, we proposed two tasks in the FIRE 2019 track on ‘Artificial Intelligence for Legal Assistance’ (AILA): (1) Identifying rel- evant prior cases for

This track defined two prob- lems such as Task 1 : Identifying relevant prior cases for a given situation and Task 2 : Identifying the most relevant statutes for a given situation..