Creative Commons and Grand Challenge to Make Legal Language Simple. - Matej Myska; Terezie Smejkalová; Jaromír Savelka; Martin Skop (AICOL, 2011)

Two Methods for Representing Judicial Reasoning in the Framework of Coherence as Constraint Satisfaction. - Michal Araszkiewicz; Jaromír Savelka (JURIX, 2011)

Refined Coherence as Constraint Satisfaction Framework for Representing Judicial Reasoning. - Michal Araszkiewicz; Jaromír Savelka (JURIX, 2012)

Coherence as Constraint Satisfaction: Judicial Reasoning Support Mechanism. - Jaromír Savelka (Coherence: Insights from Philosophy, Jurisprudence and Artificial Intelligence, 2013)

Mining Information from Statutory Texts in Multi-Jurisdictional Settings. - Jaromír Savelka; Matthias Grabmair; Kevin D. Ashley (JURIX, 2014)

Open Texture in Law, Legal Certainty and Logical Analysis of Natural Language. - Jaromír Savelka; Jakub Harasta (Logic in the Theory and Practice of Lawmaking, 2015)

Transfer of predictive models for classification of statutory texts in multi-jurisdictional settings. - Jaromír Savelka; Kevin D. Ashley (ICAIL, 2015)

Applying an Interactive Machine Learning Approach to Statutory Analysis. - Jaromír Savelka; Gaurav Trivedi; Kevin D. Ashley (JURIX, 2015)

Extracting Case Law Sentences for Argumentation about the Meaning of Statutory Terms. - Jaromír Savelka; Kevin D. Ashley (ArgMining@ACL, 2016)

Toward Linking Heterogenous References in Czech Court Decisions to Content. - Jakub Harasta; Jaromír Savelka (JURIX, 2017)

Detecting Agent Mentions in U.S. Court Decisions. - Jaromír Savelka; Kevin D. Ashley (JURIX, 2017)

Segmenting U.S. Court Decisions into Functional and Issue Specific Parts. - Jaromír Savelka; Kevin D. Ashley (JURIX, 2018)

Annotated Corpus of Czech Case Law for Reference Recognition Tasks. - Jakub Harasta; Jaromír Savelka; Frantisek Kasl; Adéla Kotková; Pavel Loutocký; Jakub Mísek; Daniela Procházková; Helena Pullmannová; Petr Semenisín; Tamara Sejnová; Nikola Simková; Michal Vosinek; et al. (TSD, 2018)

Improving Sentence Retrieval from Case Law for Statutory Interpretation. - Jaromír Savelka; Huihui Xu; Kevin D. Ashley (ICAIL, 2019)

Computer-Assisted Creation of Boolean Search Rules for Text Classification in the Legal Domain. - Hannes Westermann; Jaromír Savelka; Vern R. Walker; Kevin D. Ashley; Karim Benyekhlef (JURIX, 2019)

Paragraph Similarity Scoring and Fine-Tuned BERT for Legal Information Retrieval and Entailment. - Hannes Westermann; Jaromír Savelka; Karim Benyekhlef (JSAI-isAI Workshops, 2020)

Learning to Rank Sentences for Explaining Statutory Terms. - Jaromír Savelka; Kevin D. Ashley (ASAIL@JURIX, 2020)

Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data. - Jaromír Savelka; Hannes Westermann; Karim Benyekhlef (ASAIL@JURIX, 2020)

Sentence Embeddings and High-Speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents. - Hannes Westermann; Jaromír Savelka; Vern R. Walker; Kevin D. Ashley; Karim Benyekhlef (JURIX, 2020)

Using Argument Mining for Legal Text Summarization. - Huihui Xu; Jaromír Savelka; Kevin D. Ashley (JURIX, 2020)

Citation Data of Czech Apex Courts. - Jakub Harasta; Tereza Novotná; Jaromír Savelka (CoRR, 2020)

Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models. - Jaromír Savelka; Kevin D. Ashley (EMNLP (Findings), 2021)

Lex Rosetta: transfer of predictive models across languages, jurisdictions, and legal domains. - Jaromír Savelka; Hannes Westermann; Karim Benyekhlef; Charlotte S. Alexander; Jayla C. Grant; David Restrepo Amariles; Rajaa El Hamdani; Sébastien Meeùs; Aurore Clément Troussel; Michal Araszkiewicz; Kevin D. Ashley; Alexandra Ashley; et al. (ICAIL, 2021)

Toward summarizing case decisions via extracting argument issues, reasons, and conclusions. - Huihui Xu; Jaromír Savelka; Kevin D. Ashley (ICAIL, 2021)

Are Working Habits Different Between Well-Performing and at-Risk Students in Online Project-Based Courses? - Mingxiao An; Hongyi Zhang; Jaromír Savelka; Shijie Zhu; Chris Bogart; Majd Sakr (ITiCSE (1), 2021)

Data-Centric Machine Learning: Improving Model Performance and Understanding Through Dataset Analysis. - Hannes Westermann; Jaromír Savelka; Vern R. Walker; Kevin D. Ashley; Karim Benyekhlef (JURIX, 2021)

Accounting for Sentence Position and Legal Domain Sentence Embedding in Learning to Classify Case Sentences. - Huihui Xu; Jaromír Savelka; Kevin D. Ashley (JURIX, 2021)

Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains. - Jaromír Savelka; Hannes Westermann; Karim Benyekhlef; Charlotte S. Alexander; Jayla C. Grant; David Restrepo Amariles; Rajaa El Hamdani; Sébastien Meeùs; Michal Araszkiewicz; Kevin D. Ashley; Alexandra Ashley; Karl Branting; et al. (CoRR, 2021)

Toward Automatically Identifying Legally Relevant Factors. - Morgan A. Gray; Jaromír Savelka; Wesley M. Oliver; Kevin D. Ashley (JURIX, 2022)

Toward an Intelligent Tutoring System for Argument Mining in Legal Texts. - Hannes Westermann; Jaromír Savelka; Vern R. Walker; Kevin D. Ashley; Karim Benyekhlef (JURIX, 2022)

Legal information retrieval for understanding statutory terms. - Jaromír Savelka; Kevin D. Ashley (Artif. Intell. Law, 2022)

Data-Centric Machine Learning in the Legal Domain. - Hannes Westermann; Jaromír Savelka; Vern R. Walker; Kevin D. Ashley; Karim Benyekhlef (CoRR, 2022)

Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives. - Pragnya Sridhar; Aidan Doyle; Arav Agarwal; Christopher Bogart; Jaromír Savelka; Majd Sakr (LLM@AIED, 2023)

Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions About Code. - Jaromír Savelka; Arav Agarwal; Christopher Bogart; Majd Sakr (CSEDU (2), 2023)

Automatic Identification and Empirical Analysis of Legally Relevant Factors. - Morgan A. Gray; Jaromír Savelka; Wesley M. Oliver; Kevin D. Ashley (ICAIL, 2023)

Unlocking Practical Applications in Legal Domain: Evaluation of GPT for Zero-Shot Semantic Annotation of Legal Texts. - Jaromír Savelka (ICAIL, 2023)

Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise? - Jaromír Savelka; Kevin D. Ashley; Morgan A. Gray; Hannes Westermann; Huihui Xu (ASAIL@ICAIL, 2023)

Bridging the Gap: Mapping Layperson Narratives to Legal Issues with Language Models. - Hannes Westermann; Sébastien Meeùs; Mia Godet; Aurore Clément Troussel; Jinzhe Tan; Jaromír Savelka; Karim Benyekhlef (ASAIL@ICAIL, 2023)

LLMediator: GPT-4 Assisted Online Dispute Resolution. - Hannes Westermann; Jaromír Savelka; Karim Benyekhlef (AI4AJ@ICAIL, 2023)

Thrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Courses. - Jaromír Savelka; Arav Agarwal; Marshall An; Chris Bogart; Majd Sakr (ICER (1), 2023)

The Robots Are Here: Navigating the Generative AI Revolution in Computing Education. - James Prather; Paul Denny 001; Juho Leinonen 001; Brett A. Becker; Ibrahim Albluwi; Michelle Craig; Hieke Keuning; Natalie Kiesler; Tobias Kohn; Andrew Luxton-Reilly; Stephen MacNeil; Andrew Petersen 001; et al. (ITiCSE-WGR, 2023)

Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans. - James Prather; Paul Denny 001; Juho Leinonen 001; Brett A. Becker; Ibrahim Albluwi; Michael E. Caspersen; Michelle Craig; Hieke Keuning; Natalie Kiesler; Tobias Kohn; Andrew Luxton-Reilly; Stephen MacNeil; et al. (ITiCSE (2), 2023)

Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses? - Jaromír Savelka; Arav Agarwal; Christopher Bogart; Yifan Song; Majd Sakr (ITiCSE (1), 2023)

Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies. - Jakub Drápal; Hannes Westermann; Jaromír Savelka (JURIX, 2023)

Can GPT Alleviate the Burden of Annotation? - Morgan A. Gray; Jaromír Savelka; Wesley M. Oliver; Kevin D. Ashley (JURIX, 2023)

From Text to Structure: Using Large Language Models to Support the Development of Legal Expert Systems. - Samyar Janatian; Hannes Westermann; Jinzhe Tan; Jaromír Savelka; Karim Benyekhlef (JURIX, 2023)

CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. - Mark H. Liffiton; Brad E. Sheese; Jaromír Savelka; Paul Denny 001 (Koli Calling, 2023)

Explaining Legal Concepts with Augmented Large Language Models (GPT-4). - Jaromír Savelka; Kevin D. Ashley; Morgan A. Gray; Hannes Westermann; Huihui Xu (CoRR, 2023)

Efficient Classification of Student Help Requests in Programming Courses Using Large Language Models. - Jaromír Savelka; Paul Denny 001; Mark H. Liffiton; Brad Sheese (CoRR, 2023)

From GPT-3 to GPT-4: On the Evolving Efficacy of LLMs to Answer Multiple-choice Questions for Programming Classes in Higher Education. - Jaromír Savelka; Arav Agarwal; Christopher Bogart; Majd Sakr (CoRR, 2023)

The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts. - Jaromír Savelka; Kevin D. Ashley (Frontiers Artif. Intell., 2023)

A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education. - Jacob Doughty; Zipiao Wan; Anishka Bompelli; Jubahed Qayum; Taozhi Wang; Juran Zhang; Yujia Zheng; Aidan Doyle; Pragnya Sridhar; Arav Agarwal; Christopher Bogart; Eric Keylor; et al. (ACE, 2024)

Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant. - Brad Sheese; Mark H. Liffiton; Jaromír Savelka; Paul Denny 001 (ACE, 2024)

Examining the Trade-Offs Between Simplified and Realistic Coding Environments in an Introductory Python Programming Class. - Huy Anh Nguyen; Christopher Bogart; Jaromír Savelka; Adam Zhang; Majd Sakr (EC-TEL (1), 2024)

Desirable Characteristics for AI Teaching Assistants in Programming Education. - Paul Denny 001; Stephen MacNeil; Jaromír Savelka; Leo Porter 001; Andrew Luxton-Reilly (ITiCSE (1), 2024)

Course Delivery Methods, Student Success, and Self-efficacy in Introductory Programming. - Christopher Bogart; Can Kültür; Eric Keylor; Jaromír Savelka; Majd Sakr (ITiCSE (2), 2024)

Designing Modular Auto-graded Programming Projects. - Can Kültür; Jaromír Savelka; Christopher Bogart; Majd Sakr (ITiCSE (2), 2024)

How Instructors Incorporate Generative AI into Teaching Computing. - James Prather; Juho Leinonen 001; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Virginia Pettit; Leo Porter 001; Brent N. Reeves; Jaromír Savelka; et al. (ITiCSE (2), 2024)

Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools. - James Prather; Juho Leinonen 001; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Vee Pettit; Leo Porter 001; Brent N. Reeves; Jaromír Savelka; et al. (ITiCSE-WGR, 2024)

Using LLMs to Discover Legal Factors. - Morgan A. Gray; Jaromír Savelka; Wesley M. Oliver; Kevin D. Ashley (JURIX, 2024)

Robots in the Middle: Evaluating LLMs in Dispute Resolution. - Jinzhe Tan; Hannes Westermann; Nikhil Reddy Pottanigari; Jaromír Savelka; Sébastien Meeùs; Mia Godet; Karim Benyekhlef (JURIX, 2024)

Understanding the Role of Temperature in Diverse Question Generation by GPT-4. - Arav Agarwal; Karthik Mittal; Aidan Doyle; Pragnya Sridhar; Zipiao Wan; Jacob Arthur Doughty; Jaromír Savelka; Majd Sakr (SIGCSE (2), 2024)

What Factors Influence Persistence in Project-based Programming Courses at Community Colleges? - Christopher Bogart; Marshall An; Eric Keylor; Pawanjeet Singh; Jaromír Savelka; Majd Sakr (SIGCSE (1), 2024)

A Benchmark for Testing the Capabilities of LLMs in Assessing the Quality of Multiple-choice Questions in Introductory Programming Education. - Aninditha Ramesh; Arav Agarwal; Jacob Arthur Doughty; Ketan Ramaneti; Jaromír Savelka; Majd Sakr (SIGCSE Virtual (1), 2024)

Assessing the Efficacy of Goal-Based Scenarios in Scaling AI Literacy for Non-Technical Learners. - Ying-Jui Tseng; Ruiwei Xiao; Christopher Bogart; Jaromír Savelka; Majd Sakr (SIGCSE (2), 2024)

It Cannot Be Right If It Was Written by AI: On Lawyers' Preferences of Documents Perceived as Authored by an LLM vs a Human. - Jakub Harasta; Tereza Novotná; Jaromír Savelka (CoRR, 2024)

Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools. - James Prather; Juho Leinonen 001; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Vee Pettit; Leo Porter 001; Brent N. Reeves; Jaromír Savelka; et al. (CoRR, 2024)

Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice. - Hannes Westermann; Jaromír Savelka (CoRR, 2024)

Auto-Grader Feedback Utilization and Its Impacts: An Observational Study Across Five Community Colleges. - Adam Zhang; Heather Burte; Jaromír Savelka; Christopher Bogart; Majd Sakr (CSEDU (1), 2025)

Are Students' Evaluations of Auto-Graders Biased by Their Grades? - Yufan Zhang; Jaromír Savelka; Heather Burte; Christopher Bogart; Seth Copen Goldstein; Majd Sakr (EC-TEL (2), 2025)

Generating Distractors for Code Completion Problems: Can LLM Assist Instructors? - Mohammad Hassany; Kamil Akhuseyinoglu; Arun Balajiee Lekshmi Narayanan; Arav Agarwal; Jaromír Savelka; Peter Brusilovsky (FLAIRS, 2025)

Show Me the Mastery Learning! Obstacles to Adoption and Opportunities for New Solutions. - Claudio Álvarez; Nickolas Falkner; Päivi Kinnunen; Jaromír Savelka; Lisa Zhang (ITiCSE (1), 2025)

Can GPT4 Generate Effective Feedback on Code Readability? - Xiaotian Su; Yajie Song; Marcus Messer; Jaromír Savelka; Maria Cutumisu; April Yi Wang (ITiCSE (2), 2025)

Generating Effective Distractors for Introductory Programming Challenges: LLMs vs Humans. - Mohammad Hassany; Peter Brusilovsky; Jaromír Savelka; Arun Balajiee Lekshmi Narayanan; Kamil Akhuseyinoglu; Arav Agarwal; Rully Agus Hendrawan (LAK, 2025)

AI Technicians: Developing Rapid Occupational Training Methods for a Competitive AI Workforce. - Jaromír Savelka; Can Kültür; Arav Agarwal; Christopher Bogart; Heather Burte; Adam Zhang; Majd Sakr (SIGCSE (1), 2025)

A comparative study of AI-generated and human-crafted learning objectives in computing education. - Aidan Doyle; Pragnya Sridhar; Arav Agarwal; Jaromír Savelka; Majd Sakr (J. Comput. Assist. Learn., 2025)

Measuring Faithfulness and Abstention: An Automated Pipeline for Evaluating LLM-Generated 3-ply Case-Based Legal Arguments. - Li Zhang; Morgan A. Gray; Jaromír Savelka; Kevin D. Ashley (CoRR, 2025)