ALTARS 2024
Augmented Intelligence for Technology-Assisted Reviews Systems 2024

Table of Contents

• Preface
  Summary: There were a total of 9 papers accepted to this workshop: 2 invited papers, 2 long papers, 4 short papers, 1 abstract. All papers were peer-reviewed by at least two memebrs of the scientific committee.
• Committees

Session 1

• A Knowledge Modeling Approach for AI Applications Based on Legal Reasoning in the Semantic Web
  Enrico Francesconi

Session 2

• An Interdisciplinary Approach to Legal Terminology: Challenges of the “Algorithmic Turn” in Legal Science
  Angela Condello, Giorgio Maria Di Nunzio
• Stopping Methods Based on Point Processes: Recent Developments
  Mark Stevenson, Reem Bin-Hezam
• Towards Explainable Total Recall in TAR for eDiscovery Using Retraining of the Underlying Neural Network Model
  Charles Courchaine, Corey Wade, Tasnova Tabassum, Stetson Daisy, Ricky J. Sethi

Session 3

• Factors Affecting the Performance of Reviewers in a Large-Scale Technology-Assisted Review Project
  Maura Grossman, Gordon Cormack, Andrew Harbison, Tom O'Halloran, Bronagh McManus
• Exploring the Use of a Large Language Model for Data Extraction in Systematic Reviews: A Rapid Feasibility Study
  Lena Schmidt, Kaitlyn Hair, Sergio Graziozi, Fiona Campbell, Claudia Kapp, Alireza Khanteymoori, Dawn Craig, Mark Engelbert, James Thomas
• Leveraging Cochrane Systematic Literature Reviews for Prospective Evaluation of Large Language Models
  Wojciech Kusa, Harrisen Scells, Moritz Staudinger, Allan Hanbury

Session 4

• Extracting Information From Scientific Articles to Compile Data on Ecological Impacts of Biological Invasions
  Franck Courchamp

Final Discussion

• Technology Assisted Review Systems: Current and Future Directions
  Giorgio Maria Di Nunzio