Citation Network Analysis

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Towards Automatic Evolution Tree Generation from Citation Graphs
Sep 9, 2026Zexing Zhao, Yuntong Hu, Liang ZhaoCitation Network Analysis Bibliometric Analysis
School of Mechanical Engineering, Georgia Institute of Technology · Department of Computer Science, Emory University
A Semantic Approach to the Academic Publishing Network: Document Vector Representations and Hybrid Structural-Semantic Fusion over OpenAlex Data
Aug 11, 2026Robert Šamárek, Radek MartinekCitation Network Analysis Bibliometric Analysis
VSB – Technical University of Ostrava
GRASP: Graph-Reasoning Aided Survey Planning for High-Fidelity Related Work Generation
Jul 4, 2026Haoming Li, Jessica OuyangCitation Network Analysis Graph-Based Planning
Department of Computer Science University of Texas at Dallas Richardson, TX 75080
Reading Between the Citations: A Typed Claim Network for Scientific Literature
May 29, 2026Ning Ding, Sergio J. Rodríguez Méndez, Pouya G. OmranKG Construction Graph Retrieval-Augmented Generation
Australian National University, Canberra ACT 2601, Australia
Catalyst Papers in Artificial Intelligence Research: A Landscape on ICLR from 2017 to 2025
May 24, 2026Fan HuangCitation Network Analysis Bibliometric Analysis
Indiana University Bloomington
Automatic Construction of a Legal Citation Graph from 100 Million Ukrainian Court Decisions: Large-Scale Extraction, Topological Analysis, and Ontology-Driven Clustering
May 14, 2026Volodymyr OvcharovKG Construction Ontology Learning
LEX AI LLC, Kyiv, Ukraine
Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation
May 14, 2026Songyang Gao, Yinghui Xia, Siyi Liu +1Scientific Hypothesis Generation Citation Network Analysis
The Hong Kong University of Science and Technology (Guangzhou) · Tsinghua University · The Hong Kong University of Science and Technology
Reconnecting Fragmented Citation Networks with Semantic Augmentation
May 12, 2026Vu Thi Huong, Annika Buchholz, Imene Khebouri +5Graph Structure Learning Citation Network Analysis
Digital Data and Information for Society, Science, and Culture, Zuse Institute Berlin, Takustr. 7, 14195 Berlin, Germany · Institute of Mathematics, Vietnam Academy of Science and Technology, 10072 Hanoi, Vietnam · Software and Algorithms for Discrete Optimization, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany +2
Polarization and Integration in Global AI Research
Apr 19, 2026Luca Gallo, Riccardo Di Clemente, Balázs LengyelCitation Network Analysis
ANETI Lab, Corvinus Institute for Advanced Studies, Corvinus University of Budapest, Közrakt´ar u. 4-6, Budapest, 1093, Hungary. · Center for Social Data Science (SODAS), University of Copenhagen, Øster Farimagsgade 5A, Copenhagen, 1353, Denmark. · Complex Connections Lab, Network Science Institute, Northeastern University London, London, E1W 1LP, United Kingdom. +3
Where Do Your Citations Come From? Citation-Constellation: A Free, Open-Source, No-Code, and Auditable Tool for Citation Network Decomposition with Complementary BARON and HEROCON Scores
Mar 25, 2026Mahbub Ul AlamCitation Network Analysis Bibliometric Analysis
SciLifeLab Data Centre, Uppsala University, Sweden
Bridging Through Absence: How Comeback Researchers Bridge Knowledge Gaps Through Structural Re-emergence
Feb 25, 2026Somyajit Chakraborty, Angshuman Jana, Avijit GayenCitation Network Analysis
University College Cork, Cork, Ireland · Shanghai Jiao Tong University, Shanghai, China · Indian Institute of Information Technology, Guwahati, India +1

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Towards Automatic Evolution Tree Generation from Citation Graphs

Zexing Zhao, Yuntong Hu, Liang Zhao

School of Mechanical Engineering, Georgia Institute of Technology · Department of Computer Science, Emory University

Citation Network Analysis Bibliometric Analysis Taxonomy Induction

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Surveys remain the primary way researchers grasp the lineage of methods within an AI subfield, but they scale poorly against the current rate of publication. Existing taxonomy-induction methods are largely leaf-bound and time-agnostic; they tend to force transitional papers into mature leaves and can create topological inversions between ancestors and descendants. We propose EvoTree, a staged framework that decouples conceptual backbone learning from temporal refinement: a graph-aware encoder with distribution-based hierarchical clustering yields a stable taxonomy backbone; temporal fine-tuning then re-attaches marginal papers to internal nodes under monotonic-path constraints; a final LLM pass labels concepts without altering the topology. We release the first annotated benchmark for this task across 11 AI subfields. EvoTree attains the highest NMI and citation-direction accuracy among all baselines and the best concept purity on the annotated benchmark, and is the only method with non-trivial marginal-paper detection on the annotated set.