[2601.13969] Autonomous Knowledge Graph Exploration with Adaptive Breadth-Depth Retrieval

Computer Science > Artificial Intelligence arXiv:2601.13969 (cs) [Submitted on 20 Jan 2026 (v1), last revised 28 Apr 2026 (this version, v2)] Title:Autonomous Knowledge Graph Exploration with Adaptive Breadth-Depth Retrieval Authors:Joaquín Polonuer (1,2), Lucas Vittor (1), Iñaki Arango (1), Ayush Noori (1,3), David A. Clifton (3,4), Luciano Del Corro (5,6), Marinka Zitnik (1,7,8,9) ((1) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA, (2) Departamento de Computación, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina, (3) Department of Engineering Science, University of Oxford, Oxford, UK, (4) Oxford Suzhou Centre for Advanced Research, University of Oxford, Suzhou, Jiangsu, China, (5) ELIAS Lab, Departamento de Ingeniería, Universidad de San Andrés, Victoria, Argentina, (6) Lumina Labs, Buenos Aires, Argentina, (7) Kempner Institute for the Study of Natural and Artificial Intelligence, Allston, MA, USA, (8) Broad Institute of MIT and Harvard, Cambridge, MA, USA, (9) Harvard Data Science Initiative, Cambridge, MA, USA) View a PDF of the paper titled Autonomous Knowledge Graph Exploration with Adaptive Breadth-Depth Retrieval, by Joaqu\'in Polonuer (1 and 51 other authors View PDF HTML (experimental) Abstract:Retrieving evidence for language model queries from knowledge graphs requires balancing broad search across the graph with multi-hop traversal to follow relational links. Similarity-based retrievers provide coverage but remain sh...