8 citations · 12 across the 4 of their papers we have counts for
4 papers
Learning from Litigation: Graphs and LLMs for Retrieval and Reasoning in eDiscovery
Sounak Lahiri, Sumit Pai, Tim Weninger +1
Electronic Discovery (eDiscovery) requires identifying relevant documents from vast collections for legal production requests. While artificial intelligence (AI) and natural langua…
MatKG: The Largest Knowledge Graph in Materials Science -- Entities, Relations, and Link Prediction through Graph Representation Learning
Vineeth Venugopal, Sumit Pai, Elsa Olivetti
This paper introduces MatKG, a novel graph database of key concepts in material science spanning the traditional material-structure-property-processing paradigm. MatKG is autonomou…
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes
Sumit Pai, Luca Costabello
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, r…
Background Knowledge Injection for Interpretable Sequence Classification
Severin Gsponer, Luca Costabello, Chan Le Van +4
Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols. Although accuracy is paramount, in certain scen…