116 citations · 483 across the 23 of their papers we have counts for
25 papers
Doc2LoRA Provides Decodable Representations of Scientific Ideas
Chand Sahil Mansuri, Joel Zachariah, Sadamori Kojaku
Representing scientific papers as points in a space lets us search for similar papers and inquire about how fields relate to one another and drive innovation. Beyond search, the ve…
Multi-agent discussion gains less when dissent is withheld
Chand Sahil Mansuri, Xin Wang, Mengying Li +4
Multi-agent systems of LLMs add discussion to majority voting and are therefore expected to be more capable. However, empirical reports conflict on whether discussion improves accu…
Detectability threshold in weighted modular networks
Filippo Radicchi, Filipi N. Silva, Alessandro Flammini +2
We study the necessary condition to detect, by means of spectral modularity optimization, the ground-truth partition in networks generated according to the weighted planted-partiti…
Scale invariance and statistical significance in complex weighted networks
Filipi N. Silva, Sadamori Kojaku, Alessandro Flammini +2
Most networks encountered in nature, society, and technology have weighted edges, representing the strength of the interaction/association between their vertices. Randomizing the s…
Fast Unbiased Sampling of Networks with Given Expected Degrees and Strengths
Xuanchi Li, Xin Wang, Sadamori Kojaku
The configuration model is a cornerstone of statistical assessment of network structure. While the Chung-Lu model is among the most widely used configuration models, it systematica…
VizTrust: A Visual Analytics Tool for Capturing User Trust Dynamics in Human-AI Communication
Xin Wang, Stephanie Tulk Jesso, Sadamori Kojaku +2
Trust plays a fundamental role in shaping the willingness of users to engage and collaborate with artificial intelligence (AI) systems. Yet, measuring user trust remains challengin…
Uncovering simultaneous breakthroughs with a robust measure of disruptiveness
Munjung Kim, Sadamori Kojaku, Yong-Yeol Ahn
Progress in science and technology is punctuated by disruptive innovation and breakthroughs. Researchers have characterized these disruptions to explore the factors that spark such…
Community-centric modeling of citation dynamics explains collective citation patterns in science, law, and patents
Sadamori Kojaku, Robert Mahari, Sandro Claudio Lera +3
Many human knowledge systems, such as science, law, and invention, are built on documents and the citations that link them. Citations, while serving multiple purposes, primarily fu…
Matrix-weighted networks for modeling multidimensional dynamics
Yu Tian, Sadamori Kojaku, Hiroki Sayama +1
Networks are powerful tools for modeling interactions in complex systems. While traditional networks use scalar edge weights, many real-world systems involve multidimensional inter…
Measuring Research Interest Similarity with Transition Probabilities
Attila Varga, Sadamori Kojaku, Filipi Nascimento Silva
We introduce a family of paper and author similarity measures based on the concept that papers are more similar if they are more likely to be retrieved during a literature search f…
Implicit degree bias in the link prediction task
Rachith Aiyappa, Xin Wang, Munjung Kim +4
Link prediction -- a task of distinguishing actual hidden edges from random unconnected node pairs -- is one of the quintessential tasks in graph machine learning. Despite being wi…
Iterative embedding and reweighting of complex networks reveals community structure
Bianka Kovács, Sadamori Kojaku, Gergely Palla +1
Graph embeddings learn the structure of networks and represent it in low-dimensional vector spaces. Community structure is one of the features that are recognized and reproduced by…
Representing the Disciplinary Structure of Physics: A Comparative Evaluation of Graph and Text Embedding Methods
Isabel Constantino, Sadamori Kojaku, Santo Fortunato +1
Recent advances in machine learning offer new ways to represent and study scholarly works and the space of knowledge. Graph and text embeddings provide a convenient vector represen…
Network community detection via neural embeddings
Sadamori Kojaku, Filippo Radicchi, Yong-Yeol Ahn +1
Recent advances in machine learning research have produced powerful neural graph embedding methods, which learn useful, low-dimensional vector representations of network data. Thes…
Residual2Vec: Debiasing graph embedding with random graphs
Sadamori Kojaku, Jisung Yoon, Isabel Constantino +1
Graph embedding maps a graph into a convenient vector-space representation for graph analysis and machine learning applications. Many graph embedding methods hinge on a sampling of…
Unsupervised embedding of trajectories captures the latent structure of scientific migration
Dakota Murray, Jisung Yoon, Sadamori Kojaku +4
Human migration and mobility drives major societal phenomena including epidemics, economies, innovation, and the diffusion of ideas. Although human mobility and migration have been…
Detecting anomalous citation groups in journal networks
Sadamori Kojaku, Giacomo Livan, Naoki Masuda
The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more sele…
The effectiveness of backward contact tracing in networks
Sadamori Kojaku, Laurent Hébert-Dufresne, Enys Mones +2
Discovering and isolating infected individuals is a cornerstone of epidemic control. Because many infectious diseases spread through close contacts, contact tracing is a key tool f…
Constructing networks by filtering correlation matrices: A null model approach
Sadamori Kojaku, Naoki Masuda
Network analysis has been applied to various correlation matrix data. Thresholding on the value of the pairwise correlation is probably the most straightforward and common method t…
Multiscale core-periphery structure in a global liner shipping network
Sadamori Kojaku, Mengqiao Xu, Haoxiang Xia +1
Maritime transport accounts for a majority of trades in volume, of which 70% in value is carried by container ships that transit regular routes on fixed schedules in the ocean. In…
Configuration model for correlation matrices preserving the node strength
Naoki Masuda, Sadamori Kojaku, Yukie Sano
Correlation matrices are a major type of multivariate data. To examine properties of a given correlation matrix, a common practice is to compare the same quantity between the origi…
Structural changes in the interbank market across the financial crisis from multiple core-periphery analysis
Sadamori Kojaku, Giulio Cimini, Guido Caldarelli +1
Interbank markets are often characterised in terms of a core-periphery network structure, with a highly interconnected core of banks holding the market together, and a periphery of…
A generalised significance test for individual communities in networks
Sadamori Kojaku, Naoki Masuda
Many empirical networks have community structure, in which nodes are densely interconnected within each community (i.e., a group of nodes) and sparsely across different communities…
Core-periphery structure requires something else in the network
Sadamori Kojaku, Naoki Masuda
A network with core-periphery structure consists of core nodes that are densely interconnected. In contrast to community structure, which is a different meso-scale structure of net…