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@arXiv_csFL_bot@mastoxiv.page
2025-05-26 10:19:34

This arxiv.org/abs/2307.10434 has been replaced.
initial toot: mastoxiv.page/@arXiv_csFL_…

@macandi@social.heise.de
2025-06-23 07:54:00

Neue EU-Labels: Apple kritisiert Testmethoden, stuft iPhone und iPad herunter
In einem Paper erläutert Apple, wie die Firma mit den neuen Pflichtlabels der EU-Kommission umgeht. Das iPhone bekommt ein "B", mehrere iPads gar ein "G".

@netzschleuder@social.skewed.de
2025-07-26 19:00:03

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@datascience@genomic.social
2025-06-26 10:00:01

If you need automatic wrapping of labels in ggplot, the {ggtext} package by @clauswilke@genart.social has you covered: wilkelab.org/ggtext/articles/t But make sure you also check out the rest of the functionality of the package to add markdo…

© The British Media, forever.

The image depicts a scene from Family Guy, the animated television show. On the left side, a hand is holding a color chart with a horizontal line running through it. The chart is divided into two sections labeled "Mentally Disturbed" on the left and "Terrorist" on the right. The line is positioned between the two labels, indicating a spectrum. FOR LIGHT SKIN COLOURS = MENTALLY DISTURBED, FOR DARKER = TERRORIST The background is dark, suggesting an indoor setting, possibly a vehicle. On the righ…
@arXiv_csCL_bot@mastoxiv.page
2025-06-26 09:06:40

Perspectives in Play: A Multi-Perspective Approach for More Inclusive NLP Systems
Benedetta Muscato, Lucia Passaro, Gizem Gezici, Fosca Giannotti
arxiv.org/abs/2506.20209

@netzschleuder@social.skewed.de
2025-06-26 09:00:15

soc_net_comms: Networks with group metadata
Snapshots of LiveJournal, Friendster, Orkut, and YouTube online social networks, as well as DBLP and Amazon. Node metadata represents a post hoc definition of a 'community' that a node belongs to, derived from topical labels of the node or interest-based 'groups' that a node links to.
This network has 317080 nodes and 1049866 edges.
Tags: Online, Social, Collaboration, Informational, Relatedness, Unweighted, Metada…

soc_net_comms: Networks with group metadata. 317080 nodes, 1049866 edges. https://networks.skewed.de/net/soc_net_comms#dblp
@levi@social.linux.pizza
2025-06-20 23:54:33

Good news, everyone!
gsmarena.com/eu_energy_labels_

@arXiv_csLO_bot@mastoxiv.page
2025-07-22 08:30:00

A Proof System with Causal Labels (Part II): checking Counterfactual Fairness
Leonardo Ceragioli, Giuseppe Primiero
arxiv.org/abs/2507.14655

@arXiv_csSI_bot@mastoxiv.page
2025-06-27 07:52:09

Enhancing Homophily-Heterophily Separation: Relation-Aware Learning in Heterogeneous Graphs
Ziyu Zheng, Yaming Yang, Ziyu Guan, Wei Zhao, Weigang Lu
arxiv.org/abs/2506.20980

@cyrevolt@mastodon.social
2025-07-13 15:21:25

Folllowing the FAQ and blog, I thought I was ... stupid?
You can add labels in Draw.io - easy:
drawio.com/doc/faq/labels-add
And you should be able to rotate them, say, to fit an angled line... right?

@shoppingtonz@mastodon.social
2025-07-26 06:59:28

Neurodiversity does not seem to encourage building on science but pointing out where it went wrong.
I can commend that but I was expecting more.
What I was expecting was the people that got all these labels to do more, to develop their own out-of-the-box theories about what they discovered.
Some did and called it "neurotypes" but it never got past the medical model.
#Neurodiversity

@netzschleuder@social.skewed.de
2025-07-26 17:00:05

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 35306 edges. https://networks.skewed.de/net/malaria_genes#combined
@arXiv_csCV_bot@mastoxiv.page
2025-07-23 10:29:42

Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection
Shuang Song, Yang Tang, Rongjun Qin
arxiv.org/abs/2507.16657

@domegis@fosstodon.org
2025-07-25 14:35:51

You can use three.js as GIS to render contour lines from a Geotiff with customizable labels! Work in progress.
(P.S. can you tell where this might be? ;) ) #gischat

Contour lines
@arXiv_eessIV_bot@mastoxiv.page
2025-07-25 09:45:22

UniSegDiff: Boosting Unified Lesion Segmentation via a Staged Diffusion Model
Yilong Hu, Shijie Chang, Lihe Zhang, Feng Tian, Weibing Sun, Huchuan Lu
arxiv.org/abs/2507.18362

@arXiv_csDM_bot@mastoxiv.page
2025-07-22 07:51:50

The Labeled Coupon Collector Problem
Andrew Tan, Oriel Limor, Daniella Bar-Lev, Ryan Gabrys, Zohar Yakhini, Paul H. Siegel
arxiv.org/abs/2507.15231

@Techmeme@techhub.social
2025-06-02 21:05:43

ISP Frontier Communications settles a lawsuit from record labels that demanded broadband users accused of piracy be dropped; SCOTUS may hear Cox's similar case (Jon Brodkin/Ars Technica)
arstechnica.com/tech-policy/20

@joergi@chaos.social
2025-06-23 15:23:22

es ist leichter eine Katze als Hund zu verkaufen, als Labels, Bands und Fanzines davon zu überzeugen ins Fediverse zu kommen. #frust

@NFL@darktundra.xyz
2025-07-12 18:16:44

Tony Romo debates 'dynasty is over' labels for Chiefs, explains why Kansas City should worry opposition

cbssports.com/nfl/news/tony-ro

@arXiv_csCR_bot@mastoxiv.page
2025-06-16 07:33:39

Today's Cat Is Tomorrow's Dog: Accounting for Time-Based Changes in the Labels of ML Vulnerability Detection Approaches
Ranindya Paramitha, Yuan Feng, Fabio Massacci
arxiv.org/abs/2506.11939

@arXiv_csLO_bot@mastoxiv.page
2025-07-22 08:20:30

A Proof System with Causal Labels (Part I): checking Individual Fairness and Intersectionality
Leonardo Ceragioli, Giuseppe Primiero
arxiv.org/abs/2507.14650

@wfryer@mastodon.cloud
2025-06-23 00:51:28

Finally cancelled my Ideogram subscription today, I've had it for the past 12 months and loved it.
Now I'm using ChatGPT 4o almost exclusively for my AI image generation needs.
I updated my paid subscriptions list:
wiki.wesfryer.com/subscription

Screenshot of Ideogram.ai billing history showing a list of monthly subscription payments. The subscription changed from 'Ideogram Basic - monthly' at $8.00 on May 28, 2024, to 'Ideogram Plus - monthly' at $12.00 on May 28, 2024, and then to $20.00 starting June 28, 2024, continuing consistently through May 28, 2025. All payments are marked as 'Paid' with green labels. The Ideogram.ai logo is prominently displayed at the top in bold yellow and black text.
@digitalnaiv@mastodon.social
2025-07-22 06:23:09

Sind die „Boomer“ wirklich schuld, Millennials nur verweichlicht und Gen Z zu anspruchsvoll? Der SWR-Artikel über die Untersuchungen der Soziologin Katja Schmid räumt auf: Generationenschubladen helfen wenig, verstärken aber Vorurteile und Diskriminierung. Unterschiede gibt’s, aber die verlaufen meist quer durch alle Jahrgänge – nicht entlang erfundener Labels - Boomer, Millenials, Gen Z, Alpha? Warum es keine "Generationen" gibt

@arXiv_mathCO_bot@mastoxiv.page
2025-07-24 08:28:20

Bipartite graphs with minimum degree at least 15 are antimagic
Kecai Deng
arxiv.org/abs/2507.17302 arxiv.org/pdf/2507…

@Mediagazer@mstdn.social
2025-06-03 02:15:45

ISP Frontier Communications settles a lawsuit from record labels that demanded broadband users accused of piracy be dropped; SCOTUS may hear Cox's similar case (Jon Brodkin/Ars Technica)
arstechnica.com/tech-policy/20

@arXiv_statML_bot@mastoxiv.page
2025-06-13 09:56:20

Probably Approximately Correct Labels
Emmanuel J. Cand\`es, Andrew Ilyas, Tijana Zrnic
arxiv.org/abs/2506.10908 arxiv…

@arXiv_csIR_bot@mastoxiv.page
2025-07-08 09:44:10

Ranking-based Fusion Algorithms for Extreme Multi-label Text Classification (XMTC)
Celso Fran\c{c}a, Gestefane Rabbi, Thiago Salles, Washington Cunha, Leonardo Rocha, Marcos Andr\'e Gon\c{c}alves
arxiv.org/abs/2507.03761

@arXiv_physicschemph_bot@mastoxiv.page
2025-06-25 09:17:20

Operator Forces For Coarse-Grained Molecular Dynamics
Leon Klein, Atharva Kelkar, Aleksander Durumeric, Yaoyi Chen, Frank No\'e
arxiv.org/abs/2506.19628

@seav@en.osm.town
2025-06-19 19:04:13

Earlier this month, #TomPatterson released a free (public domain) print-quality physical map of maritime Southeast Asia. It could actually almost double as a map of SEA except the northern part of Myanmar is cut off. 🗺️

@arXiv_qbioQM_bot@mastoxiv.page
2025-06-24 08:58:20

An Analytical Neighborhood Enrichment Score for Spatial Omics
Axel Andersson, Hanna Nystr\"om
arxiv.org/abs/2506.18692

@arXiv_quantph_bot@mastoxiv.page
2025-06-23 12:20:40

Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction
Alice Barthe, Mahtab Yaghubi Rad, Michele Grossi, Vedran Dunjko
arxiv.org/abs/2506.17089

@arXiv_eessSY_bot@mastoxiv.page
2025-07-24 09:18:30

Dispatch-Aware Deep Neural Network for Optimal Transmission Switching: Toward Real-Time and Feasibility Guaranteed Operation
Minsoo Kim, Jip Kim
arxiv.org/abs/2507.17194

@markhburton@mstdn.social
2025-07-20 08:57:16

Why does the #BBC use terms like “Iran-backed Houthis” or “Hamas-run hospital,” but avoid labels such as “US-backed IDF” or referring to Israeli Prime Minister Benjamin Netanyahu as an “indicted war criminal.”?
'Why 'Hamas-run hospital' but never ‘US-backed IDF’?': Zohran Mamdani calls out double standards on Israel-Gaza coverage; slams BBC - Times of India

@arXiv_csLG_bot@mastoxiv.page
2025-06-10 19:16:59

This arxiv.org/abs/2504.11284 has been replaced.
initial toot: mastoxiv.page/@arXiv_csLG_…

@arXiv_eessAS_bot@mastoxiv.page
2025-07-25 07:46:02

ASR-Guided Speaker-Role Diarization and Diarization-Guided ASR Decoding
Arindam Ghosh, Mark Fuhs, Bongjun Kim, Anurag Chowdhury, Monika Woszczyna
arxiv.org/abs/2507.17765

@arXiv_qbiobm_bot@mastoxiv.page
2025-06-24 08:37:19

AbRank: A Benchmark Dataset and Metric-Learning Framework for Antibody-Antigen Affinity Ranking
Chunan Liu, Aurelien Pelissier, Yanjun Shao, Lilian Denzler, Andrew C. R. Martin, Brooks Paige, Mariia Rodriguez Martinez
arxiv.org/abs/2506.17857

@memeorandum@universeodon.com
2025-06-03 02:30:43

Doritos, M&Ms Could Be Forced to Include Warning Labels in Texas (Bloomberg)
bloomberg.com/news/articles/20
memeorandum.com/250602/p147#a2

@primonatura@mstdn.social
2025-07-07 18:00:57

"Switzerland Rolls Out Labels Flagging Animal Suffering In Food Products"
#Switzerland #Animals #Food

@rocket@det.social
2025-07-15 08:43:11

@… The button labels seem to be tactual, like one can identify the numbers by touching them. The labels don't. If one can't see well, that UX problem gets even harder.

@arXiv_csCL_bot@mastoxiv.page
2025-07-24 08:21:29

Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks
Giulio Pelosio, Devesh Batra, No\'emie Bovey, Robert Hankache, Cristovao Iglesias, Greig Cowan, Raad Khraishi
arxiv.org/abs/2507.16989

@arXiv_csCY_bot@mastoxiv.page
2025-07-22 11:24:31

Just Put a Human in the Loop? Investigating LLM-Assisted Annotation for Subjective Tasks
Hope Schroeder, Deb Roy, Jad Kabbara
arxiv.org/abs/2507.15821

@netzschleuder@social.skewed.de
2025-06-23 22:00:04

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@netzschleuder@social.skewed.de
2025-07-23 20:00:04

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 1446 edges. https://networks.skewed.de/net/malaria_genes#HVR_2
@pbloem@sigmoid.social
2025-07-18 09:25:22

Now out in #TMLR:
🍇 GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks 🍇
There's lots of work on sampling subgraphs for GNNs, but relatively little on making this sampling process _adaptive_. That is, learning to select the data from the graph that is relevant for your task.
We introduce an RL-based and a GFLowNet-based sampler and show that the approach perf…

A diagram of the GRAPES pipeline. It shows a subgraph being sampled in two steps and being fed to a GNN, with a blue line showing the learning signal. The caption reads Figure 1: Overview of GRAPES. First, GRAPES processes a target node (green) by computing node inclusion probabilities on its 1-hop neighbors (shown by node color shade) with a sampling GNN. Given these probabilities, GRAPES samples k nodes. Then, GRAPES repeats this process over nodes in the 2-hop neighborhood. We pass the sampl…
A results table for node classification on heterophilious graphs. Table 2: F1-scores (%) for different sampling methods trained on heterophilous graphs for a batch size of 256, and a sample size of 256 per layer. We report the mean and standard deviation over 10 runs. The best values among the sampling baselines (all except GAS) are in bold, and the second best are underlined. MC stands for multi-class and ML stands for multi-label classification. OOM indicates out of memory.
Performance of samples vs sampling size showing that GRAPES generally performs well across sample sizes, while other samplers often show more variance across sample sizes. The caption reads Figure 4: Comparative analysis of classification accuracy across different sampling sizes for sampling baseline
and GRAPES. We repeated each experiment five times: The shaded regions show the 95% confidence intervals.
A diagrammatic illustration of a graph classification task used in one of the theorems. The caption reads Figure 9: An example of a graph for Theorem 1 with eight nodes. Red edges belong to E1, features xi and labels yi are shown beside every node. For nodes v1 and v2 we show the edge e12 as an example. As shown, the label of each node is the second feature of its neighbor, where a red edge connects them. The edge homophily ratio is h=12/28 = 0.43.
@arXiv_csDS_bot@mastoxiv.page
2025-07-01 08:08:23

Near-Optimal Vertex Fault-Tolerant Labels for Steiner Connectivity
Koustav Bhanja, Asaf Petruschka
arxiv.org/abs/2506.23215

@arXiv_physicsoptics_bot@mastoxiv.page
2025-07-22 09:47:30

Label free sub-diffraction imaging using non-linear photon avalanche backlight
Suresh Karmegam, Marcin Szalkowski, Malgorzata Misiak, Katarzyna Prorok, Damian Szyma\'nski, Artur Bednarkiewicz
arxiv.org/abs/2507.14667

@arXiv_csIR_bot@mastoxiv.page
2025-07-08 10:09:30

Function-based Labels for Complementary Recommendation: Definition, Annotation, and LLM-as-a-Judge
Chihiro Yamasaki, Kai Sugahara, Yuma Nagi, Kazushi Okamoto
arxiv.org/abs/2507.03945

@stephane_klein@social.coop
2025-05-13 15:52:25

« Exemples de labels (#GitLab) de gestion de projet »
notes.sklein.xyz/2025-05-13_09

@lornajane@indieweb.social
2025-06-10 18:52:09

Them: you should probably use the keyboard layout that matches the actual labels on your keyboard
Me: …

@arXiv_eessIV_bot@mastoxiv.page
2025-06-18 08:52:12

orGAN: A Synthetic Data Augmentation Pipeline for Simultaneous Generation of Surgical Images and Ground Truth Labels
Niran Nataraj, Maina Sogabe, Kenji Kawashima
arxiv.org/abs/2506.14303

@arXiv_csSD_bot@mastoxiv.page
2025-06-19 08:36:08

Versatile Symbolic Music-for-Music Modeling via Function Alignment
Junyan Jiang, Daniel Chin, Liwei Lin, Xuanjie Liu, Gus Xia
arxiv.org/abs/2506.15548

@midtsveen@social.linux.pizza
2025-07-21 10:47:36

#GenderFluid #GenderSolid #GenderFlux #Gender

Two comic panels show a dialogue between two simplified figures. The green figure asks about genderfluid labels, and the purple figure responds about gender solid labels. Background features various pride flags. Emotions reflect confusion and contemplation.
@arXiv_statML_bot@mastoxiv.page
2025-06-11 09:55:45

Flexible and Efficient Drift Detection without Labels
Nelvin Tan, Yu-Ching Shih, Dong Yang, Amol Salunkhe
arxiv.org/abs/2506.08734

@arXiv_astrophSR_bot@mastoxiv.page
2025-06-10 17:49:10

This arxiv.org/abs/2506.02763 has been replaced.
initial toot: mastoxiv.page/@arXiv_…

@arXiv_mathCO_bot@mastoxiv.page
2025-07-22 09:18:00

Dvorak-Dell-Grohe-Rattan theorem via an asymptotic argument
Alexander Kozachinskiy
arxiv.org/abs/2507.14669 arxiv.org…

@arXiv_mathST_bot@mastoxiv.page
2025-06-12 08:35:01

Semi-supervised Community Detection using Glauber Dynamics for an Ising Model
Konstantin Avrachenkov, Diego Goldsztajn
arxiv.org/abs/2506.09223

@arXiv_csLG_bot@mastoxiv.page
2025-06-10 19:22:50

This arxiv.org/abs/2506.05047 has been replaced.
initial toot: mastoxiv.page/@arXiv_csLG_…

@arXiv_csCL_bot@mastoxiv.page
2025-07-21 09:47:50

Label Unification for Cross-Dataset Generalization in Cybersecurity NER
Maciej Jalocha, Johan Hausted Schmidt, William Michelseen
arxiv.org/abs/2507.13870

@arXiv_statML_bot@mastoxiv.page
2025-07-16 08:42:31

GOLFS: Feature Selection via Combining Both Global and Local Information for High Dimensional Clustering
Zhaoyu Xing, Yang Wan, Juan Wen, Wei Zhong
arxiv.org/abs/2507.10956

@Mediagazer@mstdn.social
2025-07-10 14:45:52

NewsGuard is retiring "misinformation" and "disinformation" as primary labels, saying the words have become meaningless and politicized (McKenzie Sadeghi/NewsGuard's Reality Check)
newsguardrealitycheck.com/p/co

@arXiv_csCV_bot@mastoxiv.page
2025-07-16 10:34:31

Attributes Shape the Embedding Space of Face Recognition Models
Pierrick Leroy, Antonio Mastropietro, Marco Nurisso, Francesco Vaccarino
arxiv.org/abs/2507.11372

@arXiv_eessIV_bot@mastoxiv.page
2025-07-21 09:10:20

Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation
Maximilian Rokuss, Benjamin Hamm, Yannick Kirchhoff, Klaus Maier-Hein
arxiv.org/abs/2507.13830

@netzschleuder@social.skewed.de
2025-07-19 18:00:04

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@arXiv_csIR_bot@mastoxiv.page
2025-07-15 09:10:12

Criteria-Based LLM Relevance Judgments
Naghmeh Farzi, Laura Dietz
arxiv.org/abs/2507.09488 arxiv.org/pdf/2507.09488…

@Techmeme@techhub.social
2025-06-01 18:25:47

Sources: UMG, Warner Music, and Sony Music are in talks to license their work to AI music services Udio and Suno and settle copyright infringement lawsuits (Lucas Shaw/Bloomberg)
bloomberg.com/news/articles/20

@arXiv_csSD_bot@mastoxiv.page
2025-06-18 09:15:39

Exploring Speaker Diarization with Mixture of Experts
Gaobin Yang, Maokui He, Shutong Niu, Ruoyu Wang, Hang Chen, Jun Du
arxiv.org/abs/2506.14750

@netzschleuder@social.skewed.de
2025-06-19 06:00:03

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@arXiv_csLG_bot@mastoxiv.page
2025-07-17 10:27:30

NOCTA: Non-Greedy Objective Cost-Tradeoff Acquisition for Longitudinal Data
Dzung Dinh, Boqi Chen, Marc Niethammer, Junier Oliva
arxiv.org/abs/2507.12412

@Mediagazer@mstdn.social
2025-07-07 17:10:33

Independent labels and trade associations urge the EU to probe UMG's $775M acquisition of music services company Downtown, saying it gives UMG too much power (Daniel Thomas/Financial Times)
ft.com/content/1c6315ba-1369-4

@arXiv_csCV_bot@mastoxiv.page
2025-07-14 10:05:02

SGPMIL: Sparse Gaussian Process Multiple Instance Learning
Andreas Lolos, Stergios Christodoulidis, Maria Vakalopoulou, Jose Dolz, Aris Moustakas
arxiv.org/abs/2507.08711

@arXiv_mathCO_bot@mastoxiv.page
2025-07-16 09:29:41

Self-reverse labelings of distance magic graphs
Petr Kov\'a\v{r}, Ksenija Rozman, Primo\v{z} \v{S}parl
arxiv.org/abs/2507.11226

@arXiv_csCL_bot@mastoxiv.page
2025-06-18 08:58:30

Probabilistic Aggregation and Targeted Embedding Optimization for Collective Moral Reasoning in Large Language Models
Chenchen Yuan, Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
arxiv.org/abs/2506.14625

@netzschleuder@social.skewed.de
2025-07-16 17:00:08

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel
@arXiv_csCV_bot@mastoxiv.page
2025-07-14 10:06:12

HieraRS: A Hierarchical Segmentation Paradigm for Remote Sensing Enabling Multi-Granularity Interpretation and Cross-Domain Transfer
Tianlong Ai, Tianzhu Liu, Haochen Jiang, Yanfeng Gu
arxiv.org/abs/2507.08741

@arXiv_eessIV_bot@mastoxiv.page
2025-06-18 08:46:15

Comparison of ConvNeXt and Vision-Language Models for Breast Density Assessment in Screening Mammography
Yusdivia Molina-Rom\'an, David G\'omez-Ortiz, Ernestina Menasalvas-Ruiz, Jos\'e Gerardo Tamez-Pe\~na, Alejandro Santos-D\'iaz
arxiv.org/abs/2506.13964

@netzschleuder@social.skewed.de
2025-07-16 02:00:17

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label
@arXiv_csIR_bot@mastoxiv.page
2025-06-18 08:30:16

Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search
Weicong Qin, Yi Xu, Weijie Yu, Teng Shi, Chenglei Shen, Ming He, Jianping Fan, Xiao Zhang, Jun Xu
arxiv.org/abs/2506.14437

@netzschleuder@social.skewed.de
2025-07-16 13:00:16

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label
@netzschleuder@social.skewed.de
2025-06-15 20:00:15

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label
@arXiv_csCL_bot@mastoxiv.page
2025-07-14 09:46:02

Distillation versus Contrastive Learning: How to Train Your Rerankers
Zhichao Xu, Zhiqi Huang, Shengyao Zhuang, Ashim Gupta, Vivek Srikumar
arxiv.org/abs/2507.08336

@arXiv_eessIV_bot@mastoxiv.page
2025-06-04 07:39:40

Dynamic mapping from static labels: remote sensing dynamic sample generation with temporal-spectral embedding
Shuai Yuan, Shuang Chen, Tianwu Lin, Jie Wang, Peng Gong
arxiv.org/abs/2506.02574

@netzschleuder@social.skewed.de
2025-07-17 12:00:04

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 2812 edges. https://networks.skewed.de/net/malaria_genes#HVR_1
@netzschleuder@social.skewed.de
2025-07-12 22:00:09

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel
@netzschleuder@social.skewed.de
2025-07-14 09:00:04

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 3961 edges. https://networks.skewed.de/net/malaria_genes#HVR_8
@netzschleuder@social.skewed.de
2025-06-13 09:00:04

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@netzschleuder@social.skewed.de
2025-07-12 06:00:03

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 3263 edges. https://networks.skewed.de/net/malaria_genes#HVR_6
@netzschleuder@social.skewed.de
2025-07-12 03:00:04

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 2812 edges. https://networks.skewed.de/net/malaria_genes#HVR_1
@netzschleuder@social.skewed.de
2025-07-10 05:00:04

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@netzschleuder@social.skewed.de
2025-07-10 01:00:04

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 7579 edges. https://networks.skewed.de/net/malaria_genes#HVR_9
@netzschleuder@social.skewed.de
2025-07-09 12:00:03

malaria_genes: Malaria var DBLa HVR networks
Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant. Metadata includes two types of node labels, both based on sequence st…

malaria_genes: Malaria var DBLa HVR networks. 307 nodes, 3263 edges. https://networks.skewed.de/net/malaria_genes#HVR_6
@netzschleuder@social.skewed.de
2025-07-06 06:00:16

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label
@netzschleuder@social.skewed.de
2025-07-07 01:00:03

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@netzschleuder@social.skewed.de
2025-06-06 20:00:04

terrorists_911: 9-11 terrorist network
Network of individuals and their known social associations, centered around the hijackers that carried out the September 11th, 2001 terrorist attacks. Associations extracted after-the-fact from public data. Metadata labels say which plane a person was on, if any, on 9/11.
This network has 62 nodes and 152 edges.
Tags: Social, Offline, Unweighted, Metadata

terrorists_911: 9-11 terrorist network. 62 nodes, 152 edges. https://networks.skewed.de/net/terrorists_911
@netzschleuder@social.skewed.de
2025-06-04 20:00:09

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel
@netzschleuder@social.skewed.de
2025-06-04 13:00:16

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label
@netzschleuder@social.skewed.de
2025-07-04 05:00:08

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel
@netzschleuder@social.skewed.de
2025-06-03 06:00:09

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel
@netzschleuder@social.skewed.de
2025-07-01 14:00:16

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

discogs_label: Discogs label affiliations. 270786 nodes, 4147665 edges. https://networks.skewed.de/net/discogs_label