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Spatial Data Science Symposium 2025 is announced. Check it out, it's hybrid!
http://sdss2025.spatial-data-science.net/index.html

Spatial Data Science Symposium 2025
December 4-5 | Distributed & Online. The symposium aims to bring together researchers from both academia and industry to discuss experiences, insights, methodologies, and applications, taking spatial and temporal knowledge into account while addressing their domain-specific problems.

Microsoft-Forscher finden TCC-Lücke in Apples Spotlight: Datenleak droht
Mit dem Exploit "Sploitlight" sollen sich unter anderem via Apple Intelligence sensible Daten abgreifen lassen. Der Bug wurde behoben, betrifft auch das iPhone.

What is "Spatial" about Spatial Computing?
Yibo Wang, Yuhan Luo, Janghee Cho, Junnan Yu
https://arxiv.org/abs/2508.20477 https://arxiv.org/pdf/25…

What is "Spatial" about Spatial Computing?
Recent advancements in geographic information systems and mixed reality technologies have positioned spatial computing as a transformative paradigm in computational science. However, the field remains conceptually fragmented, with diverse interpretations across disciplines like Human-Computer Interaction, Geographic Information Science, and Computer Science, which hinders a comprehensive understanding of spatial computing and poses challenges for its coherent advancement and interdisciplinary i…

Jerry Jones takes subtle jab at Micah Parsons for skipping practice https://www.si.com/nfl/cowboys/news/dallas-cowboys-jerry-jones-takes-subtle-jab-micah-parsons-skipping-training-camp-practice

‘He Put On Like 100lbs’: Kyle Rittenhouse Deletes Social Media Accounts and Immediately Becomes Laughingstock of the Internet After 'Finally' Disappearing from Public Spotlight
https://atlantablackstar.com/2025/06/28/kyle-rittenhouse-deletes-social-media-accounts-and-immediately-becomes-laughingstock-of-the-internet-after-finally-disappearing-from-public-spotlight/

Audiovisual integration of simple stimuli: spatial congruency effects unaffected by working memory load https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1594306/full "suggesting that it occurs at a low-level percep…

Frontiers | Audiovisual integration of simple stimuli: spatial congruency effects unaffected by working memory load
The present study sought to investigate whether working memory (WM) load influences the spatial congruency effect in audiovisual (AV) integration using simpl...

Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Jihao Gu, Kun Li, Fei Wang, Yanyan Wei, Zhiliang Wu, Hehe Fan, Meng Wang
https://arxiv.org/abs/2507.21977

Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Micro-Actions (MAs) are an important form of non-verbal communication in social interactions, with potential applications in human emotional analysis. However, existing methods in Micro-Action Recognition often overlook the inherent subtle changes in MAs, which limits the accuracy of distinguishing MAs with subtle changes. To address this issue, we present a novel Motion-guided Modulation Network (MMN) that implicitly captures and modulates subtle motion cues to enhance spatial-temporal represe…

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Supawich Sitdhipol, Waritwong Sukprasongdee, Ekapol Chuangsuwanich, Rina Tse
https://arxiv.org/abs/2507.19947

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Fusing information from human observations can help robots overcome sensing limitations in collaborative tasks. However, an uncertainty-aware fusion framework requires a grounded likelihood representing the uncertainty of human inputs. This paper presents a Feature Pyramid Likelihood Grounding Network (FP-LGN) that grounds spatial language by learning relevant map image features and their relationships with spatial relation semantics. The model is trained as a probability estimator to capture a…

Learning Robust Spatial Representations from Binaural Audio through Feature Distillation
Holger Severin Bovbjerg (Aalborg University), Jan {\O}stergaard (Aalborg University), Jesper Jensen (Aalborg University), Shinji Watanabe (Carnegie Mellon University), Zheng-Hua Tan
https://arxiv.org/abs/2508.20914…

Learning Robust Spatial Representations from Binaural Audio through Feature Distillation
Recently, deep representation learning has shown strong performance in multiple audio tasks. However, its use for learning spatial representations from multichannel audio is underexplored. We investigate the use of a pretraining stage based on feature distillation to learn a robust spatial representation of binaural speech without the need for data labels. In this framework, spatial features are computed from clean binaural speech samples to form prediction labels. These clean features are then…

🇺🇦 #NowPlaying on KEXP's #Audioasis
Magic Mouth:
🎵 Speak Softly After Dark (For Nina)
#MagicMouth
https://magicmouth.bandcamp.com/track/speak-softly-after-dark-for-nina-2
https://open.spotify.com/track/0lLge0jBAupYzOcpQNMRxE