Tootfinder

Amortizing personalization in virtual brain twins
Nina Baldy, Marmaduke M Woodman, Viktor K Jirsa
https://arxiv.org/abs/2506.21155 https://

Amortizing personalization in virtual brain twins
Virtual brain twins are personalized digital models of individual human subject or patient's brains, allowing for mechanistic interpretation of neuroimaging data features. Training and inference with these models however presents a pair of challenges: large shared infrastructure do not allow for use of personal data and inference in clinical applications should not require significant resources. We introduce "anonymized personalization" to address both by expanding model priors to include perso…

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Wanli Peng, Xin Chen, Hang Fu, XinYu He, Xue Yiming, Juan Wen
https://arxiv.org/abs/2506.19889

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Recent advances in large language models (LLMs) have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference ability of LLMs, the privacy violation attack (PVA), revealed by Staab et al., introduces serious personal privacy issues. Existing defense methods mainly leverage LLMs to anonymize the input query, which requires costly inference time and cannot gain satisfactory defense performance. Moreover, directly rejecting the PVA …

Tja.
https://newsie.social/@altpapier/114737479765334799

$(\ell,\delta)$-Diversity: Linkage-Robustness via a Composition Theorem
V. Arvind Rameshwar, Anshoo Tandon
https://arxiv.org/abs/2506.18405 https://…

$(\ell,δ)$-Diversity: Linkage-Robustness via a Composition Theorem
In this paper, we consider the problem of degradation of anonymity upon linkages of anonymized datasets. We work in the setting where an adversary links together $t\geq 2$ anonymized datasets in which a user of interest participates, based on the user's known quasi-identifiers, which motivates the use of $\ell$-diversity as the notion of dataset anonymity. We first argue that in the worst case, such linkage attacks can reveal the exact sensitive attribute of the user, even when each dataset res…

Patient-Centred Explainability in IVF Outcome Prediction
Adarsa Sivaprasad, Ehud Reiter, David McLernon, Nava Tintarev, Siladitya Bhattacharya, Nir Oren
https://arxiv.org/abs/2506.18760

Patient-Centred Explainability in IVF Outcome Prediction
This paper evaluates the user interface of an in vitro fertility (IVF) outcome prediction tool, focussing on its understandability for patients or potential patients. We analyse four years of anonymous patient feedback, followed by a user survey and interviews to quantify trust and understandability. Results highlight a lay user's need for prediction model \emph{explainability} beyond the model feature space. We identify user concerns about data shifts and model exclusions that impact trust. Th…

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Last year, I had a US intern working with us and she now is looking for help that you- good reader of this account- could give.
(She needs academic survey participants)
Check out her flyer below, click the link, and please RT
http…

Research Study on Data Privacy and Collective Redress
A researcher at University College Dublin wants to conduct anonymous interviews to learn about why you would or would not participate in a legal action to rectify a data protection violation. This information can be used to help nonprofit organizations better represent you when organizations violate your data protection rights. Provide your email to receive more information. All personally identifiable information will be deleted following completion of the study.

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
Yanjun Dai, Haoyang Feng, Yuan Gao
https://arxiv.org/abs/2506.13787

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
While online advertising is highly dependent on implicit interaction networks of anonymous users for engagement inference, and for the selection and optimization of delivery strategies, existing graph models seldom can capture the multi-scale temporal, semantic and higher-order dependency features of these interaction networks, thus it's hard to describe the complicated patterns of the anonymous behavior. In this paper, we propose Decoupled Temporal-Hierarchical Graph Neural Network (DTH-GNN), …

Le fondateur du WEF de Davos aurait piqué dans la caisse, d'où sa démission
#WEF #Davos

Grönland gibt's nicht, Liechtenstein ist verschwunden, von Neuseeland hat niemand was gehört
TAZ: Grünspan im Eismeer
Immer mehr Länder fordern geografische Anonymität und möchten mit sofortiger Wirkung von der international regulären Weltkarte gestrichen werden.
https://taz.de/Die-Wahrheit/!6091936/

Die Wahrheit: Grünspan im Eismeer
Immer mehr Länder fordern geografische Anonymität und möchten mit sofortiger Wirkung von der international regulären Weltkarte gestrichen werden.

sp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…