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Found 3 papers, 1 papers with code
Learning from Litigation: Graphs and LLMs for Retrieval and Reasoning in eDiscovery
Electronic Discovery (eDiscovery) involves identifying relevant documents from a vast collection based on legal production requests.
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes
Numeric values associated to edges of a knowledge graph have been used to represent uncertainty, edge importance, and even out-of-band knowledge in a growing number of scenarios, ranging from genetic data to social networks.
Background Knowledge Injection for Interpretable Sequence Classification
Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols.
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