Improving How We Label Legal Documents Using AI

2 Apr 2025

This study highlights the limitations in current rhetorical role labeling, particularly the single-label constraint and domain-specific evaluations.

Training AI to Understand Legal Texts in Different Domains

2 Apr 2025

Explore how rhetorical role classifiers achieve strong cross-domain generalization, even when trained on one domain and tested on others.

Enhancing Rhetorical Role Labeling with Training-Time Neighborhood Learning

2 Apr 2025

Discover how contrastive learning, discourse-aware loss, and prototypical learning enhance rhetorical role labeling.

How AI Can Better Categorize Legal Documents by Learning from Similar Texts

1 Apr 2025

Explore training-time methods like contrastive learning, single, and multi-prototype learning for rhetorical role labeling.

How Neighborhood Data Improves Legal Document Classification

1 Apr 2025

See the results of using kNN, single, and multiple prototypes for inference-based RRL, comparing performance and memory efficiency across datasets.

Improving Legal Document Labeling by Comparing Similar Sentences

1 Apr 2025

Learn how inference-based methods enhance rhetorical role labeling, improving the model’s ability to handle rare patterns in legal texts.

Leveraging Deep Learning for Legal Text Analysis

1 Apr 2025

Follow the evolution of rhetorical role labeling in legal texts, from early CRF methods to deep learning approaches, including neighborhood learning technique.

Datasets and Models Used to Analyze Legal Documents

1 Apr 2025

Explore 4 legal datasets used for rhetorical role labeling experiments and the baseline hierarchical model built on BERT and Bi-LSTM for legal judgment analysis

New AI Methods Help Machines Understand Legal Text Better

1 Apr 2025

Explore novel techniques to improve rhetorical role labeling in legal texts, addressing challenges like data scarcity, role intertwining, and cross-domain tran