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Found 6 papers, 2 papers with code
LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English
However, existing Legal NLP benchmarks only focus on predictive tasks, overlooking generative tasks.
HiCuLR: Hierarchical Curriculum Learning for Rhetorical Role Labeling of Legal Documents
Rhetorical Role Labeling (RRL) of legal documents is pivotal for various downstream tasks such as summarization, semantic case search and argument mining.
The Craft of Selective Prediction: Towards Reliable Case Outcome Classification -- An Empirical Study on European Court of Human Rights Cases
To our knowledge, this is the first systematic exploration of selective prediction in legal NLP.
Incorporating Precedents for Legal Judgement Prediction on European Court of Human Rights Cases
Inspired by the legal doctrine of stare decisis, which leverages precedents (prior cases) for informed decision-making, we explore methods to integrate them into LJP models.
Joint Span Segmentation and Rhetorical Role Labeling with Data Augmentation for Legal Documents
In this work, we reformulate the task at span level as identifying spans of multiple consecutive sentences that share the same rhetorical role label to be assigned via classification.
Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs
Specifically, we experiment with fusing embeddings obtained from knowledge graph with the state-of-the-art approaches for NLI task (ESIM model).
