36 citations · 97 across the 14 of their papers we have counts for
14 papers · 1 filter
Exploiting the Randomness of Large Language Models (LLM) in Text Classification Tasks: Locating Privileged Documents in Legal Matters
Keith Huffman, Jianping Zhang, Nathaniel Huber-Fliflet +2
In legal matters, text classification models are most often used to filter through large datasets in search of documents that meet certain pre-selected criteria like relevance to a…
Leveraging Machine Learning and Large Language Models for Automated Image Clustering and Description in Legal Discovery
Qiang Mao, Fusheng Wei, Robert Neary +4
The rapid increase in digital image creation and retention presents substantial challenges during legal discovery, digital archive, and content management. Corporations and legal t…
A Comparative Study of Retrieval Methods in Azure AI Search
Qiang Mao, Han Qin, Robert Neary +4
Increasingly, attorneys are interested in moving beyond keyword and semantic search to improve the efficiency of how they find key information during a document review task. Large…
Detecting Privileged Documents by Ranking Connected Network Entities
Jianping Zhang, Han Qin, Nathaniel Huber-Fliflet
This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata. Entities are class…
Explainable Text Classification Techniques in Legal Document Review: Locating Rationales without Using Human Annotated Training Text Snippets
Christian Mahoney, Peter Gronvall, Nathaniel Huber-Fliflet +1
US corporations regularly spend millions of dollars reviewing electronically-stored documents in legal matters. Recently, attorneys apply text classification to efficiently cull ma…
CNN Application in Detection of Privileged Documents in Legal Document Review
Rishi Chhatwal, Robert Keeling, Peter Gronvall +3
Protecting privileged communications and data from disclosure is paramount for legal teams. Legal advice, such as attorney-client communications or litigation strategy are typicall…