Tootfinder

🇺🇦 #NowPlaying on BBCRadio3's #25For25:SoundsOfTheCentury
Thea Musgrave, Johan Dalene, Nicholas Daniel, BBC Symphony Orchestra & Nil Venditti:
🎵 In Memoriam 2022
#TheaMusgrave #JohanDalene #NicholasDaniel #BBCSymphonyOrchestra #NilVenditti
#Spotify

ClustViT: Clustering-based Token Merging for Semantic Segmentation
Fabio Montello, Ronja G\"uldenring, Lazaros Nalpantidis
https://arxiv.org/abs/2510.01948 https://

ClustViT: Clustering-based Token Merging for Semantic Segmentation
Vision Transformers can achieve high accuracy and strong generalization across various contexts, but their practical applicability on real-world robotic systems is limited due to their quadratic attention complexity. Recent works have focused on dynamically merging tokens according to the image complexity. Token merging works well for classification but is less suited to dense prediction. We propose ClustViT, where we expand upon the Vision Transformer (ViT) backbone and address semantic segmen…

🇺🇦 #NowPlaying on KEXP's #MechanicalBreakdown
Mica:
🎵 Vampyr
#Mica
https://micaeternal.bandcamp.com/track/vampyr-2
https://open.spotify.com/track/2NLfaNEbc4uH0L5S4cPHx3

Suppression of inverse magnetic energy transfer in collisionless marginally magnetized plasmas
Zhuo Liu, Muni Zhou, Nuno F. G. Loureiro
https://arxiv.org/abs/2510.01573 https://…

Suppression of inverse magnetic energy transfer in collisionless marginally magnetized plasmas
We investigate the inverse cascade of magnetic energy in decaying, collisionless plasmas with moderate to high-$β$ values via first-principles numerical simulations and analytical theory. We find that pressure-anisotropy-driven instabilities, in particular the firehose instability, suppress reconnection-driven coalescence of magnetic structures (i.e., inverse transfer) by nullifying magnetic tension. This suppression leaves such structures elongated and confined to scales comparable to the Lar…

🇺🇦 #NowPlaying on #BBC6Music's #FreakZonePlaylist
Nailbomb:
🎵 Sum of Your Achievements
#Nailbomb
https://open.spotify.com/track/5zL4dDLunqmoglsOJXLctj

Depth Edge Alignment Loss: DEALing with Depth in Weakly Supervised Semantic Segmentation
Patrick Schmidt, Vasileios Belagiannis, Lazaros Nalpantidis
https://arxiv.org/abs/2509.17702

Depth Edge Alignment Loss: DEALing with Depth in Weakly Supervised Semantic Segmentation
Autonomous robotic systems applied to new domains require an abundance of expensive, pixel-level dense labels to train robust semantic segmentation models under full supervision. This study proposes a model-agnostic Depth Edge Alignment Loss to improve Weakly Supervised Semantic Segmentation models across different datasets. The methodology generates pixel-level semantic labels from image-level supervision, avoiding expensive annotation processes. While weak supervision is widely explored in tr…

🇺🇦 #NowPlaying on #BBC6Music's #AmyLamé
St. Vincent:
🎵 Pay Your Way In Pain
#StVincent
https://stvincent.bandcamp.com/track/pay-your-way-in-pain-idles-remix
https://open.spotify.com/track/1nLaoWVhNRZ38irY0LZjL6

🇺🇦 #NowPlaying on #BBC6Music's #CraigCharles
St. Vincent:
🎵 Pay Your Way In Pain
#StVincent
https://stvincent.bandcamp.com/track/pay-your-way-in-pain-idles-remix
https://open.spotify.com/track/1nLaoWVhNRZ38irY0LZjL6