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2020 – today
- 2024
[c51]Brad Sheese
, Mark H. Liffiton, Jaromír Savelka, Paul Denny:
Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant. ACE 2024: 49-57- [c50]Jacob Doughty, Zipiao Wan, Anishka Bompelli, Jubahed Qayum, Taozhi Wang, Juran Zhang, Yujia Zheng, Aidan Doyle, Pragnya Sridhar, Arav Agarwal, Christopher Bogart, Eric Keylor, Can Kültür, Jaromír Savelka, Majd Sakr:
A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education. ACE 2024: 114-123 - [c49]Huy Anh Nguyen, Christopher Bogart, Jaromír Savelka, Adam Zhang, Majd Sakr:
Examining the Trade-Offs Between Simplified and Realistic Coding Environments in an Introductory Python Programming Class. EC-TEL (1) 2024: 315-329 - [c48]Paul Denny, Stephen MacNeil, Jaromír Savelka, Leo Porter, Andrew Luxton-Reilly:
Desirable Characteristics for AI Teaching Assistants in Programming Education. ITiCSE (1) 2024 - [c47]Christopher Bogart, Can Kültür, Eric Keylor, Jaromír Savelka, Majd Sakr:
Course Delivery Methods, Student Success, and Self-efficacy in Introductory Programming. ITiCSE (2) 2024 - [c46]Can Kültür, Jaromír Savelka, Christopher Bogart, Majd Sakr:
Designing Modular Auto-graded Programming Projects. ITiCSE (2) 2024 - [c45]James Prather, Juho Leinonen, Natalie Kiesler, Jamie Gorson Benario, Sam Lau, Stephen MacNeil, Narges Norouzi, Simone Opel, Virginia Pettit, Leo Porter, Brent N. Reeves, Jaromír Savelka, David H. Smith IV, Sven Strickroth, Daniel Zingaro:
How Instructors Incorporate Generative AI into Teaching Computing. ITiCSE (2) 2024 - [c44]Christopher Bogart, Marshall An, Eric Keylor, Pawanjeet Singh, Jaromír Savelka, Majd Sakr:
What Factors Influence Persistence in Project-based Programming Courses at Community Colleges? SIGCSE (1) 2024: 116-122 - [c43]Arav Agarwal, Karthik Mittal, Aidan Doyle, Pragnya Sridhar, Zipiao Wan, Jacob Arthur Doughty, Jaromír Savelka, Majd Sakr:
Understanding the Role of Temperature in Diverse Question Generation by GPT-4. SIGCSE (2) 2024: 1550-1551 - [c42]Ying-Jui Tseng, Ruiwei Xiao, Christopher Bogart, Jaromír Savelka, Majd Sakr:
Assessing the Efficacy of Goal-Based Scenarios in Scaling AI Literacy for Non-Technical Learners. SIGCSE (2) 2024: 1842-1843 - [i29]Arav Agarwal, Karthik Mittal, Aidan Doyle, Pragnya Sridhar, Zipiao Wan, Jacob Arthur Doughty, Jaromír Savelka, Majd Sakr:
Understanding the Role of Temperature in Diverse Question Generation by GPT-4. CoRR abs/2404.09366 (2024) - [i28]Paul Denny, Stephen MacNeil, Jaromír Savelka, Leo Porter, Andrew Luxton-Reilly:
Desirable Characteristics for AI Teaching Assistants in Programming Education. CoRR abs/2405.14178 (2024) - [i27]Jakub Harasta, Tereza Novotná, Jaromír Savelka:
It Cannot Be Right If It Was Written by AI: On Lawyers' Preferences of Documents Perceived as Authored by an LLM vs a Human. CoRR abs/2407.06798 (2024) - [i26]Jinzhe Tan, Hannes Westermann, Nikhil Reddy Pottanigari, Jaromír Savelka, Sébastien Meeùs, Mia Godet, Karim Benyekhlef:
Robots in the Middle: Evaluating LLMs in Dispute Resolution. CoRR abs/2410.07053 (2024) - [i25]Morgan A. Gray, Jaromír Savelka, Wesley M. Oliver, Kevin D. Ashley:
Using LLMs to Discover Legal Factors. CoRR abs/2410.07504 (2024) - 2023
- [j2]Jaromír Savelka, Kevin D. Ashley:
The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts. Frontiers Artif. Intell. 6 (2023) - [c41]Pragnya Sridhar, Aidan Doyle, Arav Agarwal, Christopher Bogart, Jaromír Savelka, Majd Sakr:
Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives. LLM@AIED 2023: 139-150 - [c40]Jaromír Savelka, Arav Agarwal, Christopher Bogart, Majd Sakr:
Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions About Code. CSEDU (2) 2023: 47-58 - [c39]Jaromír Savelka, Kevin D. Ashley, Morgan A. Gray, Hannes Westermann, Huihui Xu:
Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise? ASAIL@ICAIL 2023: 1-12 - [c38]Hannes Westermann, Sébastien Meeùs, Mia Godet, Aurore Clément Troussel, Jinzhe Tan, Jaromír Savelka, Karim Benyekhlef:
Bridging the Gap: Mapping Layperson Narratives to Legal Issues with Language Models. ASAIL@ICAIL 2023: 37-48 - [c37]Morgan A. Gray, Jaromír Savelka, Wesley M. Oliver, Kevin D. Ashley:
Automatic Identification and Empirical Analysis of Legally Relevant Factors. ICAIL 2023: 101-110 - [c36]Jaromír Savelka:
Unlocking Practical Applications in Legal Domain: Evaluation of GPT for Zero-Shot Semantic Annotation of Legal Texts. ICAIL 2023: 447-451 - [c35]Hannes Westermann, Jaromír Savelka, Karim Benyekhlef:
LLMediator: GPT-4 Assisted Online Dispute Resolution. AI4AJ@ICAIL 2023 - [c34]Jaromír Savelka, Arav Agarwal, Marshall An, Chris Bogart, Majd Sakr:
Thrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Courses. ICER (1) 2023: 78-92 - [c33]James Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, Michelle Craig, Hieke Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, Stephen MacNeil, Andrew Petersen, Raymond Pettit, Brent N. Reeves, Jaromír Savelka:
The Robots Are Here: Navigating the Generative AI Revolution in Computing Education. ITiCSE-WGR 2023: 108-159 - [c32]Jaromír Savelka, Arav Agarwal, Christopher Bogart, Yifan Song, Majd Sakr:
Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses? ITiCSE (1) 2023: 117-123 - [c31]James Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, Michael E. Caspersen, Michelle Craig, Hieke Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, Stephen MacNeil, Andrew Petersen, Raymond Pettit, Brent N. Reeves, Jaromír Savelka:
Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans. ITiCSE (2) 2023: 561-562 - [c30]Morgan A. Gray, Jaromír Savelka, Wesley M. Oliver, Kevin D. Ashley:
Can GPT Alleviate the Burden of Annotation? JURIX 2023: 157-166 - [c29]Samyar Janatian, Hannes Westermann, Jinzhe Tan, Jaromír Savelka, Karim Benyekhlef:
From Text to Structure: Using Large Language Models to Support the Development of Legal Expert Systems. JURIX 2023: 167-176 - [c28]Jakub Drápal, Hannes Westermann, Jaromír Savelka:
Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies. JURIX 2023: 197-206 - [c27]Mark H. Liffiton, Brad E. Sheese, Jaromír Savelka, Paul Denny:
CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. Koli Calling 2023: 8:1-8:11 - [i24]Jaromír Savelka, Arav Agarwal, Christopher Bogart, Majd Sakr:
Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions about Code. CoRR abs/2303.08033 (2023) - [i23]Jaromír Savelka, Arav Agarwal, Christopher Bogart, Yifan Song, Majd Sakr:
Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses? CoRR abs/2303.09325 (2023) - [i22]Jaromír Savelka:
Unlocking Practical Applications in Legal Domain: Evaluation of GPT for Zero-Shot Semantic Annotation of Legal Texts. CoRR abs/2305.04417 (2023) - [i21]Jaromír Savelka, Kevin D. Ashley, Morgan A. Gray, Hannes Westermann, Huihui Xu:
Explaining Legal Concepts with Augmented Large Language Models (GPT-4). CoRR abs/2306.09525 (2023) - [i20]Jaromír Savelka, Arav Agarwal, Marshall An, Chris Bogart, Majd Sakr:
Thrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Courses. CoRR abs/2306.10073 (2023) - [i19]Jaromír Savelka, Kevin D. Ashley, Morgan A. Gray, Hannes Westermann, Huihui Xu:
Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise? CoRR abs/2306.13906 (2023) - [i18]Pragnya Sridhar, Aidan Doyle, Arav Agarwal, Christopher Bogart, Jaromír Savelka, Majd Sakr:
Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives. CoRR abs/2306.17459 (2023) - [i17]Hannes Westermann, Jaromír Savelka, Karim Benyekhlef:
LLMediator: GPT-4 Assisted Online Dispute Resolution. CoRR abs/2307.16732 (2023) - [i16]Mark H. Liffiton, Brad Sheese, Jaromír Savelka, Paul Denny:
CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. CoRR abs/2308.06921 (2023) - [i15]James Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, Michelle Craig, Hieke Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, Stephen MacNeil, Andrew Petersen, Raymond Pettit, Brent N. Reeves, Jaromír Savelka:
The Robots are Here: Navigating the Generative AI Revolution in Computing Education. CoRR abs/2310.00658 (2023) - [i14]Brad Sheese, Mark H. Liffiton, Jaromír Savelka, Paul Denny:
Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant. CoRR abs/2310.16984 (2023) - [i13]Jakub Drápal, Hannes Westermann, Jaromír Savelka:
Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies. CoRR abs/2310.18729 (2023) - [i12]Jaromír Savelka, Paul Denny, Mark H. Liffiton, Brad Sheese:
Efficient Classification of Student Help Requests in Programming Courses Using Large Language Models. CoRR abs/2310.20105 (2023) - [i11]Samyar Janatian, Hannes Westermann, Jinzhe Tan, Jaromír Savelka, Karim Benyekhlef:
From Text to Structure: Using Large Language Models to Support the Development of Legal Expert Systems. CoRR abs/2311.04911 (2023) - [i10]Jaromír Savelka, Arav Agarwal, Christopher Bogart, Majd Sakr:
From GPT-3 to GPT-4: On the Evolving Efficacy of LLMs to Answer Multiple-choice Questions for Programming Classes in Higher Education. CoRR abs/2311.09518 (2023) - [i9]Jacob Doughty, Zipiao Wan, Anishka Bompelli, Jubahed Qayum, Taozhi Wang, Juran Zhang, Yujia Zheng, Aidan Doyle, Pragnya Sridhar, Arav Agarwal, Christopher Bogart, Eric Keylor, Can Kültür, Jaromír Savelka, Majd Sakr:
A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education. CoRR abs/2312.03173 (2023) - 2022
- [j1]Jaromír Savelka, Kevin D. Ashley:
Legal information retrieval for understanding statutory terms. Artif. Intell. Law 30(2): 245-289 (2022) - [c26]Morgan A. Gray, Jaromír Savelka, Wesley M. Oliver, Kevin D. Ashley:
Toward Automatically Identifying Legally Relevant Factors. JURIX 2022: 53-62 - [c25]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Toward an Intelligent Tutoring System for Argument Mining in Legal Texts. JURIX 2022: 133-142 - [i8]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Data-Centric Machine Learning in the Legal Domain. CoRR abs/2201.06653 (2022) - [i7]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Toward an Intelligent Tutoring System for Argument Mining in Legal Texts. CoRR abs/2210.13635 (2022) - 2021
- [c24]Jaromír Savelka, Kevin D. Ashley:
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models. EMNLP (Findings) 2021: 4273-4283 - [c23]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, Karl Branting, Mattia Falduti, Matthias Grabmair, Jakub Harasta, Tereza Novotná, Elizabeth Tippett, Shiwanni Johnson:
Lex Rosetta: transfer of predictive models across languages, jurisdictions, and legal domains. ICAIL 2021: 129-138 - [c22]Huihui Xu, Jaromír Savelka, Kevin D. Ashley:
Toward summarizing case decisions via extracting argument issues, reasons, and conclusions. ICAIL 2021: 250-254 - [c21]Mingxiao An, Hongyi Zhang, Jaromír Savelka, Shijie Zhu, Chris Bogart, Majd Sakr:
Are Working Habits Different Between Well-Performing and at-Risk Students in Online Project-Based Courses? ITiCSE (1) 2021: 324-330 - [c20]Huihui Xu, Jaromír Savelka, Kevin D. Ashley:
Accounting for Sentence Position and Legal Domain Sentence Embedding in Learning to Classify Case Sentences. JURIX 2021: 33-42 - [c19]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Data-Centric Machine Learning: Improving Model Performance and Understanding Through Dataset Analysis. JURIX 2021: 54-57 - [i6]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Computer-Assisted Creation of Boolean Search Rules for Text Classification in the Legal Domain. CoRR abs/2112.05807 (2021) - [i5]Jaromír Savelka, Kevin D. Ashley:
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models. CoRR abs/2112.07165 (2021) - [i4]Jaromír Savelka, Hannes Westermann, Karim Benyekhlef:
Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data. CoRR abs/2112.07870 (2021) - [i3]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, Mattia Falduti, Matthias Grabmair, Jakub Harasta, Tereza Novotná, Elizabeth Tippett, Shiwanni Johnson:
Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains. CoRR abs/2112.07882 (2021) - [i2]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Sentence Embeddings and High-speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents. CoRR abs/2112.11494 (2021) - 2020
- [c18]Hannes Westermann, Jaromír Savelka, Karim Benyekhlef:
Paragraph Similarity Scoring and Fine-Tuned BERT for Legal Information Retrieval and Entailment. JSAI-isAI Workshops 2020: 269-285 - [c17]Jaromír Savelka, Kevin D. Ashley:
Learning to Rank Sentences for Explaining Statutory Terms. ASAIL@JURIX 2020 - [c16]Jaromír Savelka, Hannes Westermann, Karim Benyekhlef:
Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data. ASAIL@JURIX 2020 - [c15]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Sentence Embeddings and High-Speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents. JURIX 2020: 164-173 - [c14]Huihui Xu, Jaromír Savelka, Kevin D. Ashley:
Using Argument Mining for Legal Text Summarization. JURIX 2020: 184-193 - [i1]Jakub Harasta, Tereza Novotná, Jaromír Savelka:
Citation Data of Czech Apex Courts. CoRR abs/2002.02224 (2020)
2010 – 2019
- 2019
- [c13]Jaromír Savelka, Huihui Xu, Kevin D. Ashley:
Improving Sentence Retrieval from Case Law for Statutory Interpretation. ICAIL 2019: 113-122 - [c12]Hannes Westermann, Jaromír Savelka, Vern R. Walker, Kevin D. Ashley, Karim Benyekhlef:
Computer-Assisted Creation of Boolean Search Rules for Text Classification in the Legal Domain. JURIX 2019: 123-132 - 2018
- [c11]Jaromír Savelka, Kevin D. Ashley:
Segmenting U.S. Court Decisions into Functional and Issue Specific Parts. JURIX 2018: 111-120 - [c10]Jakub Harasta, Jaromír Savelka, Frantisek Kasl, Adéla Kotková, Pavel Loutocký, Jakub Mísek, Daniela Procházková, Helena Pullmannová, Petr Semenisín, Tamara Sejnová, Nikola Simková, Michal Vosinek, Lucie Zavadilová, Jan Zibner:
Annotated Corpus of Czech Case Law for Reference Recognition Tasks. TSD 2018: 239-250 - 2017
- [c9]Jaromír Savelka, Kevin D. Ashley:
Detecting Agent Mentions in U.S. Court Decisions. JURIX 2017: 39-48 - [c8]Jakub Harasta, Jaromír Savelka:
Toward Linking Heterogenous References in Czech Court Decisions to Content. JURIX 2017: 177-182 - 2016
- [c7]Jaromír Savelka, Kevin D. Ashley:
Extracting Case Law Sentences for Argumentation about the Meaning of Statutory Terms. ArgMining@ACL 2016 - 2015
- [c6]Jaromír Savelka, Kevin D. Ashley:
Transfer of predictive models for classification of statutory texts in multi-jurisdictional settings. ICAIL 2015: 216-220 - [c5]Jaromír Savelka, Gaurav Trivedi, Kevin D. Ashley:
Applying an Interactive Machine Learning Approach to Statutory Analysis. JURIX 2015: 101-110 - [p2]Jaromír Savelka, Jakub Harasta:
Open Texture in Law, Legal Certainty and Logical Analysis of Natural Language. Logic in the Theory and Practice of Lawmaking 2015: 159-171 - 2014
- [c4]Jaromír Savelka, Matthias Grabmair, Kevin D. Ashley:
Mining Information from Statutory Texts in Multi-Jurisdictional Settings. JURIX 2014: 133-142 - 2013
- [p1]Jaromír Savelka:
Coherence as Constraint Satisfaction: Judicial Reasoning Support Mechanism. Coherence: Insights from Philosophy, Jurisprudence and Artificial Intelligence 2013: 203-216 - [e1]Michal Araszkiewicz, Jaromír Savelka:
Coherence: Insights from Philosophy, Jurisprudence and Artificial Intelligence. Springer 2013, ISBN 978-94-007-6109-4 [contents] - 2012
- [c3]Michal Araszkiewicz, Jaromír Savelka:
Refined Coherence as Constraint Satisfaction Framework for Representing Judicial Reasoning. JURIX 2012: 1-10 - 2011
- [c2]Matej Myska, Terezie Smejkalová, Jaromír Savelka, Martin Skop:
Creative Commons and Grand Challenge to Make Legal Language Simple. AICOL 2011: 271-285 - [c1]Michal Araszkiewicz, Jaromír Savelka:
Two Methods for Representing Judicial Reasoning in the Framework of Coherence as Constraint Satisfaction. JURIX 2011: 165-166
Coauthor Index
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