activity
20212026
most citedGerman BERT Model for Legal Named Entity Recognition

28 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

Bundesrecht: An Open Library and Corpus for German Statutory Reference Processing

Harshil Darji, Martin Heckelmann, Christina Kratsch +1

Statutory references are central to legal language understanding, but are difficult to process automatically, as they appear in compact and variable surface forms, may combine mult…

cs.CL2026★ 1 cited

Segmentation and Processing of German Court Decisions from Open Legal Data

Harshil Darji, Martin Heckelmann, Christina Kratsch +1

The availability of structured legal data is important for advancing Natural Language Processing (NLP) techniques for the German legal system. One of the most widely used datasets,…

cs.LG2024

Investigating Sparsity in Recurrent Neural Networks

Harshil Darji

In the past few years, neural networks have evolved from simple Feedforward Neural Networks to more complex neural networks, such as Convolutional Neural Networks and Recurrent Neu…

cs.IR2024

Challenges and Considerations in Annotating Legal Data: A Comprehensive Overview

Harshil Darji, Jelena Mitrović, Michael Granitzer

The process of annotating data within the legal sector is filled with distinct challenges that differ from other fields, primarily due to the inherent complexities of legal languag…

cs.CL2023★ 28 cited

German BERT Model for Legal Named Entity Recognition

Harshil Darji, Jelena Mitrović, Michael Granitzer

The use of BERT, one of the most popular language models, has led to improvements in many Natural Language Processing (NLP) tasks. One such task is Named Entity Recognition (NER) i…

cs.LG2021

Experiments on Properties of Hidden Structures of Sparse Neural Networks

Julian Stier, Harshil Darji, Michael Granitzer

Sparsity in the structure of Neural Networks can lead to less energy consumption, less memory usage, faster computation times on convenient hardware, and automated machine learning…