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@netzschleuder@social.skewed.de
2025-06-08 16:00:13

corporate_directors: Global corporate directors (2016)
Bipartite network of directors and the companies on whose boards they sit, spanning 54 countries worldwide, constructed from data collected by the Financial Times (c. Sept. 2016). Person nodes are annotated with age and gender. Company nodes are annotated with their country, sector, industry, and number of employees.
This network has 356638 nodes and 377060 edges.
Tags: Economic, Governance, Unweighted, Metadata

corporate_directors: Global corporate directors (2016). 356638 nodes, 377060 edges. https://networks.skewed.de/net/corporate_directors
@arXiv_csLG_bot@mastoxiv.page
2025-06-09 10:12:32

Antithetic Noise in Diffusion Models
Jing Jia, Sifan Liu, Bowen Song, Wei Yuan, Liyue Shen, Guanyang Wang
arxiv.org/abs/2506.06185

@arXiv_eessIV_bot@mastoxiv.page
2025-06-09 08:20:42

DermaCon-IN: A Multi-concept Annotated Dermatological Image Dataset of Indian Skin Disorders for Clinical AI Research
Shanawaj S Madarkar, Mahajabeen Madarkar, Madhumitha V, Teli Prakash, Konda Reddy Mopuri, Vinaykumar MV, KVL Sathwika, Adarsh Kasturi, Gandla Dilip Raj, PVN Supranitha, Harsh Udai
arxiv.org/abs/2506.06099…

@_mr_moe@mastodon.social
2025-05-08 06:52:26

Bundesamt für Verfassungsschutz: Hier sind die ersten Belege zur Verfassungsfeindlichkeit der AfD fragdenstaat.de/artikel/exklus

@Techmeme@techhub.social
2025-06-02 22:35:46

After Google's two antitrust losses in the past year, a look at critics' claims that its breakup might be better for investors, customers, and innovation (David Streitfeld/New York Times)
nytimes.com…

@arXiv_csCV_bot@mastoxiv.page
2025-06-09 10:05:22

STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving
Christian Fruhwirth-Reisinger, Du\v{s}an Mali\'c, Wei Lin, David Schinagl, Samuel Schulter, Horst Possegger
arxiv.org/abs/2506.06218

@netzschleuder@social.skewed.de
2025-06-08 13:00:04

us_agencies: U.S. government agency websites (2018)
50 networks, one for each U.S. state, representing the web-based links between their associated government agencies websites. A node is an entire agency website and a directed edge (i,j) represents the existence of a hyperlink from any webpage in website i to some webpage in website j. Data was collected with a crawler. Nodes are annotated with the number of webpages per website, website name (related to its government function) and U…

us_agencies: U.S. government agency websites (2018). 1079 nodes, 11238 edges. https://networks.skewed.de/net/us_agencies#texas
@arXiv_csLG_bot@mastoxiv.page
2025-06-09 10:13:32

Model-Driven Graph Contrastive Learning
Ali Azizpour, Nicolas Zilberstein, Santiago Segarra
arxiv.org/abs/2506.06212

@arXiv_csCV_bot@mastoxiv.page
2025-06-09 10:05:52

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study
Leon Mayer, Tim R\"adsch, Dominik Michael, Lucas Luttner, Amine Yamlahi, Evangelia Christodoulou, Patrick Godau, Marcel Knopp, Annika Reinke, Fiona Kolbinger, Lena Maier-Hein
arxiv.org/abs/2506.06232

@netzschleuder@social.skewed.de
2025-06-05 19:00:30

eu_procurements: EU procurement contract networks (2008-2016)
A bipartite network of public EU procurement contracts, from 2008 to 2016, between issuing buyers (public institutions such as a ministry or city hall) and supplying winners (a private firm). Contracts are aggregated into annual snapshots, edges are annotated with contract value information. Nodes are annotated with location information, including country of origin.
This network has 839824 nodes and 4098711 edges.

eu_procurements: EU procurement contract networks (2008-2016). 839824 nodes, 4098711 edges. https://networks.skewed.de/net/eu_procurements