Tootfinder

Demonstranten worden geframed als schuldig aan het geweld dat juist gepleegd wordt door agenten…
https://www.groene.nl/arti…

Duitse Palestina-demonstraties stuiten op steeds fellere repressie
Berlijn – Terwijl de wereldwijde kritiek op het geweld in Gaza toeneemt en het dodental oploopt, leidt Duitslands krampachtige verhouding tot Israël tot steeds fellere repressie van solidariteit met Palestina.

paris_transportation: Paris Transportation (2016)
A multiplex transportation network of Ile-de-France, jointly representing the road network, train network, and subway network. Nodes are intersections, rail stations or metro stations. Different modes of transportation are given by different layers. Within-layer edges represent direct transference by a particular mode of transportation, and between-layer edges represent the conjunction of those layers at that node.
This network ha…

heise | Roborock in Home Assistant einbinden: Staubsauger smart steuern
Wer seinen Roborock-Roboter in Home Assistant integriert, kann neue Features hinzufügen, Reinigungen automatisch starten und ihn per Dashboard steuern.

TACO Trump Reverses Course, Directs Bondi to Produce Meaningless Epstein Files - WhoWhatWhy
https://whowhatwhy.org/politics/us-politics/taco-trump-reverses-course-directs-bondi-to-produce-meaningless-epstein-files/

Improving Accuracy and Efficiency of Implicit Neural Representations: Making SIREN a WINNER
Hemanth Chandravamsi, Dhanush V. Shenoy, Steven H. Frankel
https://arxiv.org/abs/2509.12980

Improving Accuracy and Efficiency of Implicit Neural Representations: Making SIREN a WINNER
We identify and address a fundamental limitation of sinusoidal representation networks (SIRENs), a class of implicit neural representations. SIRENs Sitzmann et al. (2020), when not initialized appropriately, can struggle at fitting signals that fall outside their frequency support. In extreme cases, when the network's frequency support misaligns with the target spectrum, a 'spectral bottleneck' phenomenon is observed, where the model yields to a near-zero output and fails to recover even the fr…

Event2Vec: A Geometric Approach to Learning Composable Representations of Event Sequences
Antonin Sulc
https://arxiv.org/abs/2509.12188 https://arxiv.org/p…

Event2Vec: A Geometric Approach to Learning Composable Representations of Event Sequences
The study of neural representations, both in biological and artificial systems, is increasingly revealing the importance of geometric and topological structures. Inspired by this, we introduce Event2Vec, a novel framework for learning representations of discrete event sequences. Our model leverages a simple, additive recurrent structure to learn composable, interpretable embeddings. We provide a theoretical analysis demonstrating that, under specific training objectives, our model's learned rep…

Language models align with brain regions that represent concepts across modalities
Maria Ryskina, Greta Tuckute, Alexander Fung, Ashley Malkin, Evelina Fedorenko
https://arxiv.org/abs/2508.11536

Language models align with brain regions that represent concepts across modalities
Cognitive science and neuroscience have long faced the challenge of disentangling representations of language from representations of conceptual meaning. As the same problem arises in today's language models (LMs), we investigate the relationship between LM--brain alignment and two neural metrics: (1) the level of brain activation during processing of sentences, targeting linguistic processing, and (2) a novel measure of meaning consistency across input modalities, which quantifies how consiste…

paris_transportation: Paris Transportation (2016)
A multiplex transportation network of Ile-de-France, jointly representing the road network, train network, and subway network. Nodes are intersections, rail stations or metro stations. Different modes of transportation are given by different layers. Within-layer edges represent direct transference by a particular mode of transportation, and between-layer edges represent the conjunction of those layers at that node.
This network ha…

Collapse of Irrelevant Representations (CIR) Ensures Robust and Non-Disruptive LLM Unlearning
Filip Sondej, Yushi Yang
https://arxiv.org/abs/2509.11816 https://

Collapse of Irrelevant Representations (CIR) Ensures Robust and Non-Disruptive LLM Unlearning
Current unlearning techniques and safety training consistently fail to remove dangerous knowledge from language models. We analyze the root causes and propose a highly selective technique which unlearns robustly and without disrupting general performance. We perform PCA on activations and module output gradients to identify subspaces containing common representations, and collapse them before calculating unlearning updates. This way we avoid unlearning general representations, and only target…

A Global Dataset of Location Data Integrity-Assessed Reforestation Efforts
Angela John, Selvyn Allotey, Till Koebe, Alexandra Tyukavina, Ingmar Weber
https://arxiv.org/abs/2508.11349

A Global Dataset of Location Data Integrity-Assessed Reforestation Efforts
Afforestation and reforestation are popular strategies for mitigating climate change by enhancing carbon sequestration. However, the effectiveness of these efforts is often self-reported by project developers, or certified through processes with limited external validation. This leads to concerns about data reliability and project integrity. In response to increasing scrutiny of voluntary carbon markets, this study presents a dataset on global afforestation and reforestation efforts compiled fr…