23 citations · 74 across the 10 of their papers we have counts for
10 papers
Question-Answering Approach to Evaluating Legal Summaries
Huihui Xu, Kevin Ashley
Traditional evaluation metrics like ROUGE compare lexical overlap between the reference and generated summaries without taking argumentative structure into account, which is import…
Argumentative Segmentation Enhancement for Legal Summarization
Huihui Xu, Kevin Ashley
We use the combination of argumentative zoning [1] and a legal argumentative scheme to create legal argumentative segments. Based on the argumentative segmentation, we propose a no…
Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Jaromir Savelka, Kevin D. Ashley, Morgan A. Gray +2
Interpreting the meaning of legal open-textured terms is a key task of legal professionals. An important source for this interpretation is how the term was applied in previous cour…
Toward an Intelligent Tutoring System for Argument Mining in Legal Texts
Hannes Westermann, Jaromir Savelka, Vern R. Walker +2
We propose an adaptive environment (CABINET) to support caselaw analysis (identifying key argument elements) based on a novel cognitive computing framework that carefully matches v…
Multi-granularity Argument Mining in Legal Texts
Huihui Xu, Kevin Ashley
In this paper, we explore legal argument mining using multiple levels of granularity. Argument mining has usually been conceptualized as a sentence classification problem. In this…
Data-Centric Machine Learning in the Legal Domain
Hannes Westermann, Jaromir Savelka, Vern R. Walker +2
Machine learning research typically starts with a fixed data set created early in the process. The focus of the experiments is finding a model and training procedure that result in…
Sentence Embeddings and High-speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents
Hannes Westermann, Jaromir Savelka, Vern R. Walker +2
Human-performed annotation of sentences in legal documents is an important prerequisite to many machine learning based systems supporting legal tasks. Typically, the annotation is…
Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains
Jaromir Savelka, Hannes Westermann, Karim Benyekhlef +15
In this paper, we examine the use of multi-lingual sentence embeddings to transfer predictive models for functional segmentation of adjudicatory decisions across jurisdictions, leg…
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models
Jaromir Savelka, Kevin D. Ashley
Legal texts routinely use concepts that are difficult to understand. Lawyers elaborate on the meaning of such concepts by, among other things, carefully investigating how have they…
Computer-Assisted Creation of Boolean Search Rules for Text Classification in the Legal Domain
Hannes Westermann, Jaromir Savelka, Vern R. Walker +2
In this paper, we present a method of building strong, explainable classifiers in the form of Boolean search rules. We developed an interactive environment called CASE (Computer As…