4 papers
Millions of -s: Extending GraphRAG to Millions of Documents
Zhili Shen, Chenxin Diao, Pascual Merita +2
Recent studies have explored graph-based approaches to retrieval-augmented generation, leveraging structured or semi-structured information -- such as entities and their relations…
Positioning AI Tools to Support Online Harm Reduction Practice: Applications and Design Directions
Kaixuan Wang, Jason T. Jacques, Chenxin Diao +1
Access to accurate and actionable harm reduction information can directly impact the health outcomes of People Who Use Drugs (PWUD), yet existing online channels often fail to meet…
GeAR: Graph-enhanced Agent for Retrieval-augmented Generation
Zhili Shen, Chenxin Diao, Pavlos Vougiouklis +12
Retrieval-augmented Generation (RAG) relies on effective retrieval capabilities, yet traditional sparse and dense retrievers inherently struggle with multi-hop retrieval scenarios.…
From An LLM Swarm To A PDDL-Empowered HIVE: Planning Self-Executed Instructions In A Multi-Modal Jungle
Kaustubh Vyas, Damien Graux, Yijun Yang +8
In response to the call for agent-based solutions that leverage the ever-increasing capabilities of the deep models' ecosystem, we introduce Hive -- a comprehensive solution for kn…