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Machine Learning-Based Real-Time Indoor Landmark Localization.

, , , and . WWIC, volume 10866 of Lecture Notes in Computer Science, page 95-106. Springer, (2018)

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Can we Pretrain a SotA Legal Language Model on a Budget From Scratch?, and . SustaiNLP, page 158-182. Association for Computational Linguistics, (2023)Machine Learning-Based Real-Time Indoor Landmark Localization., , , and . WWIC, volume 10866 of Lecture Notes in Computer Science, page 95-106. Springer, (2018)MultiLegalSBD: A Multilingual Legal Sentence Boundary Detection Dataset., , and . ICAIL, page 42-51. ACM, (2023)Challenging Human Supremacy: Evaluating Monte Carlo Tree Search and Deep Learning for the Trick Taking Card Game Jass., , , , and . ICAISC (2), volume 12416 of Lecture Notes in Computer Science, page 505-517. Springer, (2020)Automatic Anonymization of Swiss Federal Supreme Court Rulings., , , , and . CoRR, (2023)Resolving Legalese: A Multilingual Exploration of Negation Scope Resolution in Legal Documents., , , and . LREC/COLING, page 13992-14004. ELRA and ICCL, (2024)LegalLens: Leveraging LLMs for Legal Violation Identification in Unstructured Text., , , , , , , and . EACL (1), page 2129-2145. Association for Computational Linguistics, (2024)ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the US., , , , and . NLLP@EMNLP, page 31-46. Association for Computational Linguistics, (2022)Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset., , , , and . LREC/COLING, page 16500-16513. ELRA and ICCL, (2024)FLawN-T5: An Empirical Examination of Effective Instruction-Tuning Data Mixtures for Legal Reasoning., , , , , , , , , and . CoRR, (2024)