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References from NER in the courtroom: A data-driven framework for legal entity extraction. Local targets link to admitted publications; unresolved targets remain external evidence.
The application of pre-trained transformer models to UK court of appeal legal judgments
2025 · External reference
Unresolved reference
2024 · External reference
Natural language processing for the legal domain: A survey of tasks, datasets, models, and challenges
10.1145/3777009 · 2025 · External reference
Unsupervised statistical machine translation
2018 · External reference
AI ethics in predictive policing: From models of threat to an ethics of care
10.1109/mts.2019.2915154 · 2019 · External reference
Impact of word embedding models on text analytics in deep learning environment: A review
10.1007/s10462-023-10419-1 · 2023 · External reference
E-NER — an annotated named entity recognition corpus of legal text
2022 · External reference
Interactive question answering systems: Literature review
10.1145/3657631 · 2024 · External reference
Language models are few-shot learners
2020 · External reference
Unresolved reference
2024 · External reference
Qlora: Efficient finetuning of quantized llms
10.52202/075280-0441 · 2023 · External reference
Informed named entity recognition decoding for generative language models
2024 · External reference
A comparative study of large language models for named entity recognition in the legal domain
2024 · External reference
A review of semi-supervised learning for text classification
10.1007/s10462-023-10393-8 · 2023 · External reference
Named entity recognition and classification in historical documents: A survey
10.1145/3604931 · 2023 · External reference
Unsupervised named-entity extraction from the Web: An experimental study
10.1016/j.artint.2005.03.001 · 2005 · External reference
Lawbench: Benchmarking legal knowledge of large language models
2024 · External reference
Unresolved reference
2008 · External reference
Bringing order into the realm of transformer-based language models for artificial intelligence and law
2023 · External reference
Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models
2023 · External reference
DODFMiner: An automated tool for named entity recognition from official gazettes
10.1016/j.neucom.2023.127064 · 2024 · External reference
Retrieval augmented language model pre-training
2020 · External reference
Lora: Low-rank adaptation of large language models
2022 · External reference
Location reference recognition from texts: A survey and comparison
10.1145/3625819 · 2023 · External reference
Tender document analyzer with the combination of supervised learning and LLM-based improver
2024 · External reference
The global landscape of AI ethics guidelines
10.1038/s42256-019-0088-2 · 2019 · External reference
Corpus for automatic structuring of legal documents
10.63317/543m4q3q6ts6 · 2022 · External reference
LegNER: A domain-adapted transformer for legal named entity recognition and text anonymization
10.3389/frai.2025.1638971 · 2025 · External reference
Unresolved reference
2023 · External reference
A survey on event-based news narrative extraction
10.1145/3584741 · 2023 · External reference
A survey on challenges and advances in natural language processing with a focus on legal informatics and low-resource languages
10.3390/electronics13030648 · 2024 · External reference
Large language models (LLMs): Survey, technical frameworks, and future challenges
10.1007/s10462-024-10888-y · 2024 · External reference
Sparse conditional hidden Markov model for weakly supervised named entity recognition
2022 · External reference
A survey on deep learning for named entity recognition
10.1109/tkde.2020.2981314 · 2022 · External reference
A survey on deep learning for named entity recognition : Extended abstract
2023 · External reference
Character-level neural network model based on nadam optimization and its application in clinical concept extraction
10.1016/j.neucom.2020.07.027 · 2020 · External reference
Unresolved reference
2023 · External reference
ITALIAN-LEGAL-BERT models for improving natural language processing tasks in the Italian legal domain
10.1016/j.clsr.2023.105908 · 2024 · External reference
A rigorous study on named entity recognition: Can fine-tuning pretrained model lead to the promised land?
2020 · External reference
Lost in the middle: How language models use long contexts
10.1162/tacl_a_00638 · 2024 · External reference
Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
10.52202/068431-0142 · 2022 · External reference
Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
2022 · External reference
Concept representation by learning explicit and implicit concept couplings
10.1109/mis.2020.3021188 · 2021 · External reference
Unresolved reference
2022 · External reference
Recent advances in natural language processing via large pre-trained language models: A survey
10.1145/3605943 · 2023 · External reference
Unresolved reference
2021 · External reference
Few-shot named entity recognition: Definition, taxonomy and research directions
2023 · External reference
Human-in-the-loop machine learning: A state of the art
10.1007/s10462-022-10246-w · 2023 · External reference
Named entity recognition and relation extraction: State-of-the-art
10.1145/3445965 · 2021 · External reference
Unresolved reference
2023 · External reference
True few-shot learning with language models
2021 · External reference
Unresolved reference
2024 · External reference
Exploring the limits of transfer learning with a unified text-to-text transformer
2020 · External reference
QA dataset explosion: A taxonomy of NLP resources for question answering and reading comprehension
10.1145/3560260 · 2023 · External reference
Sentence boundary detection in legal text
2019 · External reference
Legal information retrieval systems: State-of-the-art and open issues
10.1016/j.is.2021.101967 · 2022 · External reference
Pushing the limits of low-resource NER using LLM artificial data generation
2024 · External reference
A weak supervision approach with adversarial training for named entity recognition
2021 · External reference
Unresolved reference
2024 · External reference
Unresolved reference
2023 · External reference
10.63317/23ofday96scm
10.63317/23ofday96scm · External reference
Using sensitive data to prevent discrimination by artificial intelligence: Does the GDPR need a new exception?
10.1016/j.clsr.2022.105770 · 2023 · External reference
Using language models for extracting legal decisions from portuguese consumer law texts
2025 · External reference
A novel large-language-model-driven framework for named entity recognition
10.1016/j.ipm.2024.104054 · 2025 · External reference
Utilizing BERT for information retrieval: Survey, applications, resources, and challenges
10.1145/3648471 · 2024 · External reference
GPT-NER: Named entity recognition via large language models
2025 · External reference
Nested named entity recognition: A survey
2022 · External reference
10.63317/36og6fywzqzc
10.63317/36og6fywzqzc · External reference
Unresolved reference
2021 · External reference
10.1145/3539618.3591852
10.1145/3539618.3591852 · External reference
Extracting complex named entities in legal documents via weakly supervised object detection
2023 · External reference
Harnessing the power of LLMs in practice: A survey on ChatGPT and beyond
2024 · External reference
Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts
10.1016/j.jbi.2013.08.004 · 2013 · External reference
SecLMNER: A framework for enhanced named entity recognition in multi-source cybersecurity data using large language models
10.1016/j.eswa.2025.126651 · 2025 · External reference
A survey on syntactic processing techniques
10.1007/s10462-022-10300-7 · 2023 · External reference
Unresolved reference
2024 · External reference
How does NLP benefit legal system: A summary of legal artificial intelligence
2020 · External reference
Unresolved reference
2023 · External reference
Human-in-the-loop machine learning: A state of the art
10.1007/s10462-022-10246-w · ExternalCitation · doi-reference
A survey on syntactic processing techniques
10.1007/s10462-022-10300-7 · ExternalCitation · doi-reference
A review of semi-supervised learning for text classification
10.1007/s10462-023-10393-8 · ExternalCitation · doi-reference
Impact of word embedding models on text analytics in deep learning environment: A review
10.1007/s10462-023-10419-1 · ExternalCitation · doi-reference
Large language models (LLMs): Survey, technical frameworks, and future challenges
10.1007/s10462-024-10888-y · ExternalCitation · doi-reference
Unsupervised named-entity extraction from the Web: An experimental study
10.1016/j.artint.2005.03.001 · ExternalCitation · doi-reference
Using sensitive data to prevent discrimination by artificial intelligence: Does the GDPR need a new exception?
10.1016/j.clsr.2022.105770 · ExternalCitation · doi-reference
ITALIAN-LEGAL-BERT models for improving natural language processing tasks in the Italian legal domain
10.1016/j.clsr.2023.105908 · ExternalCitation · doi-reference
SecLMNER: A framework for enhanced named entity recognition in multi-source cybersecurity data using large language models
10.1016/j.eswa.2025.126651 · ExternalCitation · doi-reference
A novel large-language-model-driven framework for named entity recognition
10.1016/j.ipm.2024.104054 · ExternalCitation · doi-reference
Legal information retrieval systems: State-of-the-art and open issues
10.1016/j.is.2021.101967 · ExternalCitation · doi-reference
Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts
10.1016/j.jbi.2013.08.004 · ExternalCitation · doi-reference
Character-level neural network model based on nadam optimization and its application in clinical concept extraction
10.1016/j.neucom.2020.07.027 · ExternalCitation · doi-reference
DODFMiner: An automated tool for named entity recognition from official gazettes
10.1016/j.neucom.2023.127064 · ExternalCitation · doi-reference
The global landscape of AI ethics guidelines
10.1038/s42256-019-0088-2 · ExternalCitation · doi-reference
Concept representation by learning explicit and implicit concept couplings
10.1109/mis.2020.3021188 · ExternalCitation · doi-reference
AI ethics in predictive policing: From models of threat to an ethics of care
10.1109/mts.2019.2915154 · ExternalCitation · doi-reference
A survey on deep learning for named entity recognition
10.1109/tkde.2020.2981314 · ExternalCitation · doi-reference
Named entity recognition and relation extraction: State-of-the-art
10.1145/3445965 · ExternalCitation · doi-reference
10.1145/3539618.3591852
10.1145/3539618.3591852 · ExternalCitation · doi-reference
QA dataset explosion: A taxonomy of NLP resources for question answering and reading comprehension
10.1145/3560260 · ExternalCitation · doi-reference
A survey on event-based news narrative extraction
10.1145/3584741 · ExternalCitation · doi-reference
Named entity recognition and classification in historical documents: A survey
10.1145/3604931 · ExternalCitation · doi-reference
Recent advances in natural language processing via large pre-trained language models: A survey
10.1145/3605943 · ExternalCitation · doi-reference
Location reference recognition from texts: A survey and comparison
10.1145/3625819 · ExternalCitation · doi-reference
Utilizing BERT for information retrieval: Survey, applications, resources, and challenges
10.1145/3648471 · ExternalCitation · doi-reference
Interactive question answering systems: Literature review
10.1145/3657631 · ExternalCitation · doi-reference
Natural language processing for the legal domain: A survey of tasks, datasets, models, and challenges
10.1145/3777009 · ExternalCitation · doi-reference
Lost in the middle: How language models use long contexts
10.1162/tacl_a_00638 · ExternalCitation · doi-reference
LegNER: A domain-adapted transformer for legal named entity recognition and text anonymization
10.3389/frai.2025.1638971 · ExternalCitation · doi-reference
A survey on challenges and advances in natural language processing with a focus on legal informatics and low-resource languages
10.3390/electronics13030648 · ExternalCitation · doi-reference
Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
10.52202/068431-0142 · ExternalCitation · doi-reference
Qlora: Efficient finetuning of quantized llms
10.52202/075280-0441 · ExternalCitation · doi-reference
10.63317/23ofday96scm
10.63317/23ofday96scm · ExternalCitation · doi-reference
10.63317/36og6fywzqzc
10.63317/36og6fywzqzc · ExternalCitation · doi-reference
Corpus for automatic structuring of legal documents
10.63317/543m4q3q6ts6 · ExternalCitation · doi-reference
