Matthias Grabmair

发表

TRANSFER LEARNING IN NATURAL LANGUAGE PRO-

A. Tomasic, Mihir Kale, Aditya Siddhant, 2019 .

Towards Measurable Intelligent Inference Position paper on the future of legal argumentation with cases in AI & Law

Matthias Grabmair, 2013 .

Thirty years of Artificial Intelligence and Law: the first decade

Trevor J. M. Bench-Capon, Bart Verheij, E. Francesconi, 2022, Artificial Intelligence and Law.

Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts

Matthias Grabmair, O. Ichim, T. Santosh, 2022, EMNLP.

Automatic Summarization of Legal Decisions using Iterative Masking of Predictive Sentences

Kevin D. Ashley, Linwu Zhong, Ziyi Zhong, 2019, ICAIL.

Lex Rosetta: transfer of predictive models across languages, jurisdictions, and legal domains

Kevin D. Ashley, Matthias Grabmair, Tereza Novotná, 2021, ICAIL.

Sentence Boundary Detection in Adjudicatory Decisions in the United States

Kevin D. Ashley, Matthias Grabmair, Vern R. Walker, 2017, TAL.

Mining Information from Statutory Texts in Multi-Jurisdictional Settings

Kevin D. Ashley, Matthias Grabmair, Jaromír Savelka, 2014, JURIX.

Context-aware legal citation recommendation using deep learning

Matthias Grabmair, Daniel E. Ho, Mengqiu Teng, 2021, ICAIL.

Introducing LUIMA: an experiment in legal conceptual retrieval of vaccine injury decisions using a UIMA type system and tools

Chen Wang, Kevin D. Ashley, Ran Chen, 2015, ICAIL.

Joint Span Segmentation and Rhetorical Role Labeling with Data Augmentation for Legal Documents

Matthias Grabmair, Santosh T.Y.S.S, Philipp Bock, 2023, ECIR.

Toward Extracting Information from Public Health Statutes using Text Classification Machine Learning

Kevin D. Ashley, Matthias Grabmair, Rebecca Hwa, 2011, JURIX.

Predicting trade secret case outcomes using argument schemes and learned quantitative value effect tradeoffs

Matthias Grabmair, Matthias Grabmair, 2017, ICAIL.

Using event progression to enhance purposive argumentation in the value judgment formalism

Kevin D. Ashley, Matthias Grabmair, Matthias Grabmair, 2013, ICAIL.

Facilitating case comparison using value judgments and intermediate legal concepts

Kevin D. Ashley, Matthias Grabmair, Matthias Grabmair, 2011, ICAIL.

Using critical questions to disambiguate and formalize statutory provisions

Kevin D. Ashley, Matthias Grabmair, Matthias Grabmair, 2009, ICAIL.

Probabilistic Semantics for the Carneades Argument Model Using Bayesian Networks

Matthias Grabmair, Douglas Walton, Thomas F. Gordon, 2010, COMMA.

How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing

Matthias Grabmair, Eric Nyberg, Thomas Manzini, 2017, SIGDIAL Conference.

Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance

Matthias Grabmair, Shanshan Xu, Abhishek Agarwal, 2022, EMNLP.

Introduction for artificial intelligence and law: special issue “natural language processing for legal texts”

Serena Villata, Livio Robaldo, Matthias Grabmair, 2019, Artificial Intelligence and Law.

Segmentation of Rulemaking Documentsfor Public Notice-and-Comment Process Analysis

Matthias Grabmair, Eric Nyberg, Anna Belova, 2019, AIAS@ICAIL.

Question answering via web extracted tables

Matthias Grabmair, Fan Hu, Suhail Barot, 2019, aiDM@SIGMOD.

Document Ranking with Citation Information and Oversampling Sentence Classification in the LUIMA Framework

Kevin D. Ashley, Matthias Grabmair, Silun Wang, 2016, JURIX.

A Law School Course in Applied Legal Analytics and AI

Kevin D. Ashley, Matthias Grabmair, Jaromir Savelka, 2021, Law in Context. A Socio-legal Journal.

Towards Inference-Oriented Reading Comprehension: ParallelQA pdf

Matthias Grabmair, Eric Nyberg, Soumya Wadhwa, 2018, ArXiv.

VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights

Matthias Grabmair, O. Ichim, Shanshan Xu, 2023, Conference on Empirical Methods in Natural Language Processing.

From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification

Matthias Grabmair, O. Ichim, Shanshan Xu, 2023, EMNLP.

Zero-shot Transfer of Article-aware Legal Outcome Classification for European Court of Human Rights Cases

Matthias Grabmair, O. Ichim, Santosh T.Y.S.S, 2023, FINDINGS.

Leveraging Task Dependency and Contrastive Learning for Case Outcome Classification on European Court of Human Rights Cases

Matthias Grabmair, Santosh T.Y.S.S, Phillip Kemper, 2023, EACL.

Mind Your Neighbours: Leveraging Analogous Instances for Rhetorical Role Labeling for Legal Documents

Matthias Grabmair, Santosh T.Y.S.S, Hassan Sarwat, 2024, 2404.01344.

Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification

Matthias Grabmair, O. Ichim, Shanshan Xu, 2024, arXiv.org.

Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance

Matthias Grabmair, Shanshan Xu, Abhishek Agarwal, 2022, EMNLP.

LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English

Matthias Grabmair, Santosh T.Y.S.S, Cornelius Weiss, 2024, NLLP.

LexAbSumm: Aspect-based Summarization of Legal Decisions

Matthias Grabmair, Santosh T.Y.S.S, Mahmoud Aly, 2024, LREC.