1 citations · 2 across the 2 of their papers we have counts for
4 papers
Inside CORE-KG: Evaluating Structured Prompting and Coreference Resolution for Knowledge Graphs
Dipak Meher, Carlotta Domeniconi
Human smuggling networks are increasingly adaptive and difficult to analyze. Legal case documents offer critical insights but are often unstructured, lexically dense, and filled wi…
LINK-KG: LLM-Driven Coreference-Resolved Knowledge Graphs for Human Smuggling Networks
Dipak Meher, Carlotta Domeniconi, Guadalupe Correa-Cabrera
Human smuggling networks are complex and constantly evolving, making them difficult to analyze comprehensively. Legal case documents offer rich factual and procedural insights into…
CORE-KG: An LLM-Driven Knowledge Graph Construction Framework for Human Smuggling Networks
Dipak Meher, Carlotta Domeniconi, Guadalupe Correa-Cabrera
Human smuggling networks are increasingly adaptive and difficult to analyze. Legal case documents offer valuable insights but are unstructured, lexically dense, and filled with amb…
Cross-Domain Recommendation Meets Large Language Models
Ajay Krishna Vajjala, Dipak Meher, Ziwei Zhu +1
Cross-domain recommendation (CDR) has emerged as a promising solution to the cold-start problem, faced by single-domain recommender systems. However, existing CDR models rely on co…