1 citations · 1 across the 2 of their papers we have counts for
4 papers
Granite Embedding Multilingual R2 Models
Parul Awasthy, Aashka Trivedi, Yushu Yang +14
We introduce the multilingual Granite Embedding R2 models, a family of encoder-based embedding models for enterprise-scale dense retrieval across 200+ languages. Extending our Engl…
Granite Embedding R2 Models
Parul Awasthy, Aashka Trivedi, Yulong Li +17
We introduce the Granite Embedding R2 models, a comprehensive family of high-performance English encoder-based embedding models engineered for enterprise-scale dense retrieval appl…
Distilling Event Sequence Knowledge From Large Language Models
Somin Wadhwa, Oktie Hassanzadeh, Debarun Bhattacharjya +2
Event sequence models have been found to be highly effective in the analysis and prediction of events. Building such models requires availability of abundant high-quality event seq…
An Evaluation Framework for Mapping News Headlines to Event Classes in a Knowledge Graph
Steve Fonin Mbouadeu, Martin Lorenzo, Ken Barker +1
Mapping ongoing news headlines to event-related classes in a rich knowledge base can be an important component in a knowledge-based event analysis and forecasting solution. In this…